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For: Quince C, Walker AW, Simpson JT, Loman NJ, Segata N. Shotgun metagenomics, from sampling to analysis. Nat Biotechnol 2017;35:833-44. [PMID: 28898207 DOI: 10.1038/nbt.3935] [Cited by in Crossref: 522] [Cited by in F6Publishing: 399] [Article Influence: 104.4] [Reference Citation Analysis]
Number Citing Articles
1 Liu H, Hsu T, Wu Y, Huang C. Unraveling microbiomes associated with decomposition of needles of two Pinus species with contrasting fire-adaptive strategies. Biol Fertil Soils 2021;57:715-29. [DOI: 10.1007/s00374-021-01564-2] [Reference Citation Analysis]
2 Bulow C, Langdon A, Hink T, Wallace M, Reske KA, Patel S, Sun X, Seiler S, Jones S, Kwon JH, Burnham CA, Dantas G, Dubberke ER. Impact of Amoxicillin-Clavulanate followed by Autologous Fecal Microbiota Transplantation on Fecal Microbiome Structure and Metabolic Potential. mSphere 2018;3:e00588-18. [PMID: 30463925 DOI: 10.1128/mSphereDirect.00588-18] [Cited by in Crossref: 11] [Cited by in F6Publishing: 5] [Article Influence: 2.8] [Reference Citation Analysis]
3 Pinto D, Trink A, Sorbellini E, Giuliani G, Rinaldi F. 'Omics' approaches for studying the microbiome in Alopecia areata. J Investig Med 2020;68:1292-4. [PMID: 32958525 DOI: 10.1136/jim-2020-001426] [Reference Citation Analysis]
4 Chiu CY, Miller SA. Clinical metagenomics. Nat Rev Genet 2019;20:341-55. [PMID: 30918369 DOI: 10.1038/s41576-019-0113-7] [Cited by in Crossref: 212] [Cited by in F6Publishing: 183] [Article Influence: 70.7] [Reference Citation Analysis]
5 Mallawaarachchi VG, Wickramarachchi AS, Lin Y. Improving metagenomic binning results with overlapped bins using assembly graphs. Algorithms Mol Biol 2021;16:3. [PMID: 33947431 DOI: 10.1186/s13015-021-00185-6] [Reference Citation Analysis]
6 Garcia-Grau I, Simon C, Moreno I. Uterine microbiome-low biomass and high expectations†. Biol Reprod 2019;101:1102-14. [PMID: 30544156 DOI: 10.1093/biolre/ioy257] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
7 Zhou P, Manoil D, Belibasakis GN, Kotsakis GA. Veillonellae: Beyond Bridging Species in Oral Biofilm Ecology. Front Oral Health 2021;2:774115. [PMID: 35048073 DOI: 10.3389/froh.2021.774115] [Reference Citation Analysis]
8 Hu W, Pan J, Wang B, Guo J, Li M, Xu M. Metagenomic insights into the metabolism and evolution of a new Thermoplasmata order (Candidatus Gimiplasmatales). Environ Microbiol 2021;23:3695-709. [PMID: 33295091 DOI: 10.1111/1462-2920.15349] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
9 Hernández M, Quijada NM, Rodríguez-Lázaro D, Eiros JM. [Bioinformatics of next generation sequencing in clinical microbiology diagnosis]. Rev Argent Microbiol 2020;52:150-61. [PMID: 31784184 DOI: 10.1016/j.ram.2019.06.003] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 Bovo S, Ribani A, Utzeri VJ, Schiavo G, Bertolini F, Fontanesi L. Shotgun metagenomics of honey DNA: Evaluation of a methodological approach to describe a multi-kingdom honey bee derived environmental DNA signature. PLoS One 2018;13:e0205575. [PMID: 30379893 DOI: 10.1371/journal.pone.0205575] [Cited by in Crossref: 17] [Cited by in F6Publishing: 10] [Article Influence: 4.3] [Reference Citation Analysis]
11 Traving SJ, Balmonte JP, Seale D, Arnosti C, Glud RN, Hallam SJ, Middelboe M. On Single-Cell Enzyme Assays in Marine Microbial Ecology and Biogeochemistry. Front Mar Sci 2022;9:846656. [DOI: 10.3389/fmars.2022.846656] [Reference Citation Analysis]
12 Doster E, Rovira P, Noyes NR, Burgess BA, Yang X, Weinroth MD, Lakin SM, Dean CJ, Linke L, Magnuson R, Jones KI, Boucher C, Ruiz J, Belk KE, Morley PS. Investigating Effects of Tulathromycin Metaphylaxis on the Fecal Resistome and Microbiome of Commercial Feedlot Cattle Early in the Feeding Period. Front Microbiol 2018;9:1715. [PMID: 30105011 DOI: 10.3389/fmicb.2018.01715] [Cited by in Crossref: 18] [Cited by in F6Publishing: 14] [Article Influence: 4.5] [Reference Citation Analysis]
13 Suchodolski JS. Analysis of the gut microbiome in dogs and cats. Vet Clin Pathol 2021. [PMID: 34514619 DOI: 10.1111/vcp.13031] [Reference Citation Analysis]
14 Parente E, Ricciardi A, Zotta T. The microbiota of dairy milk: A review. International Dairy Journal 2020;107:104714. [DOI: 10.1016/j.idairyj.2020.104714] [Cited by in Crossref: 21] [Cited by in F6Publishing: 3] [Article Influence: 10.5] [Reference Citation Analysis]
15 Zhang L, Wang Y, Chen J, Chen J. RFtest: A Robust and Flexible Community-Level Test for Microbiome Data Powerfully Detects Phylogenetically Clustered Signals. Front Genet 2022;12:749573. [DOI: 10.3389/fgene.2021.749573] [Reference Citation Analysis]
16 Wang W, Nettleton JE, Gänzle MG, Reimer RA. A Metagenomics Investigation of Intergenerational Effects of Non-nutritive Sweeteners on Gut Microbiome. Front Nutr 2022;8:795848. [DOI: 10.3389/fnut.2021.795848] [Reference Citation Analysis]
17 Zaouri N, Jumat MR, Cheema T, Hong PY. Metagenomics-based evaluation of groundwater microbial profiles in response to treated wastewater discharge. Environ Res 2020;180:108835. [PMID: 31655333 DOI: 10.1016/j.envres.2019.108835] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 2.3] [Reference Citation Analysis]
18 Wang Y, Hu Y, Gao GF. Combining metagenomics and metatranscriptomics to study human, animal and environmental resistomes. Medicine in Microecology 2020;3:100014. [DOI: 10.1016/j.medmic.2020.100014] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
19 Milani C, Alessandri G, Mangifesta M, Mancabelli L, Lugli GA, Fontana F, Longhi G, Anzalone R, Viappiani A, Duranti S, Turroni F, Costi R, Annicchiarico A, Morini A, Sarli L, Ossiprandi MC, van Sinderen D, Ventura M. Untangling Species-Level Composition of Complex Bacterial Communities through a Novel Metagenomic Approach. mSystems 2020;5:e00404-20. [PMID: 32723792 DOI: 10.1128/mSystems.00404-20] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
20 Vuong P, Wise MJ, Whiteley AS, Kaur P. Small investments with big returns: environmental genomic bioprospecting of microbial life. Crit Rev Microbiol 2022;:1-15. [PMID: 35100064 DOI: 10.1080/1040841X.2021.2011833] [Reference Citation Analysis]
21 Tarallo S, Ferrero G, Gallo G, Francavilla A, Clerico G, Realis Luc A, Manghi P, Thomas AM, Vineis P, Segata N, Pardini B, Naccarati A, Cordero F. Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples. mSystems 2019;4:e00289-19. [PMID: 31530647 DOI: 10.1128/mSystems.00289-19] [Cited by in Crossref: 23] [Cited by in F6Publishing: 16] [Article Influence: 7.7] [Reference Citation Analysis]
22 Peters DL, Wang W, Zhang X, Ning Z, Mayne J, Figeys D. Metaproteomic and Metabolomic Approaches for Characterizing the Gut Microbiome. Proteomics 2019;19:e1800363. [PMID: 31321880 DOI: 10.1002/pmic.201800363] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 3.0] [Reference Citation Analysis]
23 Ankersen DV, Weimers P, Bennedsen M, Haaber AB, Fjordside EL, Beber ME, Lieven C, Saboori S, Vad N, Rannem T, Marker D, Paridaens K, Frahm S, Jensen L, Rosager Hansen M, Burisch J, Munkholm P. Long-Term Effects of a Web-Based Low-FODMAP Diet Versus Probiotic Treatment for Irritable Bowel Syndrome, Including Shotgun Analyses of Microbiota: Randomized, Double-Crossover Clinical Trial. J Med Internet Res 2021;23:e30291. [PMID: 34904950 DOI: 10.2196/30291] [Reference Citation Analysis]
24 Li J, Ma X, Chakravarti D, Shalapour S, DePinho RA. Genetic and biological hallmarks of colorectal cancer. Genes Dev 2021;35:787-820. [PMID: 34074695 DOI: 10.1101/gad.348226.120] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Peel N, Dicks LV, Clark MD, Heavens D, Percival‐alwyn L, Cooper C, Davies RG, Leggett RM, Yu DW, Freckleton R. Semi‐quantitative characterisation of mixed pollen samples using MinION sequencing and Reverse Metagenomics (RevMet). Methods Ecol Evol 2019;10:1690-701. [DOI: 10.1111/2041-210x.13265] [Cited by in Crossref: 14] [Article Influence: 4.7] [Reference Citation Analysis]
26 Thongbunrod N, Chaiprasert P. Efficacy and Metagenomic Analysis of the Stabilized Anaerobic Lignocellulolytic Microbial Consortium from Bubalus bubalis Rumen with Rice Straw Enrichment for Methane Production. Bioenerg Res 2021;14:870-90. [DOI: 10.1007/s12155-020-10167-y] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
27 Wu C, Chen T, Xu W, Zhang T, Pei Y, Yang Y, Zhang F, Guo H, Wang Q, Wang L, Zhao B. The maintenance of microbial community in human fecal samples by a cost effective preservation buffer. Sci Rep 2021;11:13453. [PMID: 34188136 DOI: 10.1038/s41598-021-92869-7] [Reference Citation Analysis]
28 Jégousse C, Vannier P, Groben R, Glöckner FO, Marteinsson V. A total of 219 metagenome-assembled genomes of microorganisms from Icelandic marine waters. PeerJ 2021;9:e11112. [PMID: 33859876 DOI: 10.7717/peerj.11112] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
29 Kirisits MJ, Emelko MB, Pinto AJ. Applying biotechnology for drinking water biofiltration: advancing science and practice. Current Opinion in Biotechnology 2019;57:197-204. [DOI: 10.1016/j.copbio.2019.05.009] [Cited by in Crossref: 13] [Cited by in F6Publishing: 6] [Article Influence: 4.3] [Reference Citation Analysis]
30 Sulaiman I, Schuster S, Segal LN. Perspectives in lung microbiome research. Curr Opin Microbiol 2020;56:24-9. [PMID: 32623064 DOI: 10.1016/j.mib.2020.06.001] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
31 Li M, Yang L, Mu C, Sun Y, Gu Y, Chen D, Liu T, Cao H. Gut Microbial Metabolome in Inflammatory Bowel Disease: from Association to Therapeutic Perspectives. Computational and Structural Biotechnology Journal 2022. [DOI: 10.1016/j.csbj.2022.03.038] [Reference Citation Analysis]
32 Joseph TA, Pe'er I. An Introduction to Whole-Metagenome Shotgun Sequencing Studies. Methods Mol Biol 2021;2243:107-22. [PMID: 33606255 DOI: 10.1007/978-1-0716-1103-6_6] [Reference Citation Analysis]
33 Worsley-Tonks KEL, Miller EA, Gehrt SD, McKenzie SC, Travis DA, Johnson TJ, Craft ME. Characterization of antimicrobial resistance genes in Enterobacteriaceae carried by suburban mesocarnivores and locally owned and stray dogs. Zoonoses Public Health 2020;67:460-6. [PMID: 32034890 DOI: 10.1111/zph.12691] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
34 Chan AW, Naphtali J, Schellhorn HE. High-throughput DNA sequencing technologies for water and wastewater analysis. Sci Prog 2019;102:351-76. [PMID: 31818206 DOI: 10.1177/0036850419881855] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
35 Bovo S, Utzeri VJ, Ribani A, Cabbri R, Fontanesi L. Shotgun sequencing of honey DNA can describe honey bee derived environmental signatures and the honey bee hologenome complexity. Sci Rep 2020;10:9279. [PMID: 32518251 DOI: 10.1038/s41598-020-66127-1] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 3.5] [Reference Citation Analysis]
36 Lee KA, Thomas AM, Bolte LA, Björk JR, de Ruijter LK, Armanini F, Asnicar F, Blanco-Miguez A, Board R, Calbet-Llopart N, Derosa L, Dhomen N, Brooks K, Harland M, Harries M, Leeming ER, Lorigan P, Manghi P, Marais R, Newton-Bishop J, Nezi L, Pinto F, Potrony M, Puig S, Serra-Bellver P, Shaw HM, Tamburini S, Valpione S, Vijay A, Waldron L, Zitvogel L, Zolfo M, de Vries EGE, Nathan P, Fehrmann RSN, Bataille V, Hospers GAP, Spector TD, Weersma RK, Segata N. Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma. Nat Med 2022;28:535-44. [PMID: 35228751 DOI: 10.1038/s41591-022-01695-5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Pasolli E, Asnicar F, Manara S, Zolfo M, Karcher N, Armanini F, Beghini F, Manghi P, Tett A, Ghensi P, Collado MC, Rice BL, DuLong C, Morgan XC, Golden CD, Quince C, Huttenhower C, Segata N. Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle. Cell 2019;176:649-662.e20. [PMID: 30661755 DOI: 10.1016/j.cell.2019.01.001] [Cited by in Crossref: 483] [Cited by in F6Publishing: 345] [Article Influence: 161.0] [Reference Citation Analysis]
38 Sun J, Huang T, Debelius JW, Fang F. Gut microbiome and amyotrophic lateral sclerosis: A systematic review of current evidence. J Intern Med 2021. [PMID: 34080741 DOI: 10.1111/joim.13336] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
39 Asnicar F, Berry SE, Valdes AM, Nguyen LH, Piccinno G, Drew DA, Leeming E, Gibson R, Le Roy C, Khatib HA, Francis L, Mazidi M, Mompeo O, Valles-Colomer M, Tett A, Beghini F, Dubois L, Bazzani D, Thomas AM, Mirzayi C, Khleborodova A, Oh S, Hine R, Bonnett C, Capdevila J, Danzanvilliers S, Giordano F, Geistlinger L, Waldron L, Davies R, Hadjigeorgiou G, Wolf J, Ordovás JM, Gardner C, Franks PW, Chan AT, Huttenhower C, Spector TD, Segata N. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat Med 2021;27:321-32. [PMID: 33432175 DOI: 10.1038/s41591-020-01183-8] [Cited by in Crossref: 44] [Cited by in F6Publishing: 43] [Article Influence: 44.0] [Reference Citation Analysis]
40 Ahannach S, Delanghe L, Spacova I, Wittouck S, Van Beeck W, De Boeck I, Lebeer S. Microbial enrichment and storage for metagenomics of vaginal, skin, and saliva samples. iScience 2021;24:103306. [PMID: 34765924 DOI: 10.1016/j.isci.2021.103306] [Reference Citation Analysis]
41 Sala C, Mordhorst H, Grützke J, Brinkmann A, Petersen TN, Poulsen C, Cotter PD, Crispie F, Ellis RJ, Castellani G, Amid C, Hakhverdyan M, Guyader SL, Manfreda G, Mossong J, Nitsche A, Ragimbeau C, Schaeffer J, Schlundt J, Tay MYF, Aarestrup FM, Hendriksen RS, Pamp SJ, De Cesare A. Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community. Microorganisms 2020;8:E1861. [PMID: 33255715 DOI: 10.3390/microorganisms8121861] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
42 Alberdi A, Aizpurua O, Bohmann K, Gopalakrishnan S, Lynggaard C, Nielsen M, Gilbert MTP. Promises and pitfalls of using high‐throughput sequencing for diet analysis. Mol Ecol Resour 2019;19:327-48. [DOI: 10.1111/1755-0998.12960] [Cited by in Crossref: 55] [Cited by in F6Publishing: 27] [Article Influence: 13.8] [Reference Citation Analysis]
43 Tiew PY, Thng KX, Chotirmall SH. Clinical Aspergillus Signatures in COPD and Bronchiectasis. JoF 2022;8:480. [DOI: 10.3390/jof8050480] [Reference Citation Analysis]
44 Knight R, Vrbanac A, Taylor BC, Aksenov A, Callewaert C, Debelius J, Gonzalez A, Kosciolek T, Mccall L, Mcdonald D, Melnik AV, Morton JT, Navas J, Quinn RA, Sanders JG, Swafford AD, Thompson LR, Tripathi A, Xu ZZ, Zaneveld JR, Zhu Q, Caporaso JG, Dorrestein PC. Best practices for analysing microbiomes. Nat Rev Microbiol 2018;16:410-22. [DOI: 10.1038/s41579-018-0029-9] [Cited by in Crossref: 529] [Cited by in F6Publishing: 443] [Article Influence: 132.3] [Reference Citation Analysis]
45 King WL, Jenkins C, Seymour JR, Labbate M. Oyster disease in a changing environment: Decrypting the link between pathogen, microbiome and environment. Mar Environ Res 2019;143:124-40. [PMID: 30482397 DOI: 10.1016/j.marenvres.2018.11.007] [Cited by in Crossref: 28] [Cited by in F6Publishing: 21] [Article Influence: 7.0] [Reference Citation Analysis]
46 Han D, Diao Z, Lai H, Han Y, Xie J, Zhang R, Li J. Multilaboratory assessment of metagenomic next-generation sequencing for unbiased microbe detection. Journal of Advanced Research 2021. [DOI: 10.1016/j.jare.2021.09.011] [Reference Citation Analysis]
47 Toole DR, Zhao J, Martens-habbena W, Strauss SL. Bacterial functional prediction tools detect but underestimate metabolic diversity compared to shotgun metagenomics in southwest Florida soils. Applied Soil Ecology 2021;168:104129. [DOI: 10.1016/j.apsoil.2021.104129] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
48 Rick EM, Woolnough KF, Seear PJ, Fairs A, Satchwell J, Richardson M, Monteiro WR, Craner M, Bourne M, Wardlaw AJ, Pashley CH. The airway fungal microbiome in asthma. Clin Exp Allergy 2020;50:1325-41. [PMID: 32808353 DOI: 10.1111/cea.13722] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
49 Afshari R, Pillidge CJ, Dias DA, Osborn AM, Gill H. Cheesomics: the future pathway to understanding cheese flavour and quality. Critical Reviews in Food Science and Nutrition 2020;60:33-47. [DOI: 10.1080/10408398.2018.1512471] [Cited by in Crossref: 21] [Cited by in F6Publishing: 17] [Article Influence: 5.3] [Reference Citation Analysis]
50 Luo X, Shen L, Meng F. Response of Microbial Community Structures and Functions of Nitrosifying Consortia to Biorefractory Humic Substances. ACS Sustainable Chem Eng 2019;7:4744-54. [DOI: 10.1021/acssuschemeng.8b04853] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 3.7] [Reference Citation Analysis]
51 Tett A, Pasolli E, Masetti G, Ercolini D, Segata N. Prevotella diversity, niches and interactions with the human host. Nat Rev Microbiol 2021;19:585-99. [PMID: 34050328 DOI: 10.1038/s41579-021-00559-y] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
52 [DOI: 10.1101/2020.11.19.388223] [Cited by in Crossref: 21] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
53 Seyler L, Kujawinski EB, Azua-Bustos A, Lee MD, Marlow J, Perl SM, Cleaves Ii HJ. Metabolomics as an Emerging Tool in the Search for Astrobiologically Relevant Biomarkers. Astrobiology 2020;20:1251-61. [PMID: 32551936 DOI: 10.1089/ast.2019.2135] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
54 Mabwi HA, Kim E, Song DG, Yoon HS, Pan CH, Komba EVG, Ko G, Cha KH. Synthetic gut microbiome: Advances and challenges. Comput Struct Biotechnol J 2021;19:363-71. [PMID: 33489006 DOI: 10.1016/j.csbj.2020.12.029] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
55 Boscaini S, Cabrera-Rubio R, Nychyk O, Roger Speakman J, Francis Cryan J, David Cotter P, Nilaweera KN. Age- and duration-dependent effects of whey protein on high-fat diet-induced changes in body weight, lipid metabolism, and gut microbiota in mice. Physiol Rep 2020;8:e14523. [PMID: 32748559 DOI: 10.14814/phy2.14523] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
56 Zizka VMA, Koschorreck J, Khan CC, Astrin JJ. Long-term archival of environmental samples empowers biodiversity monitoring and ecological research. Environ Sci Eur 2022;34. [DOI: 10.1186/s12302-022-00618-y] [Reference Citation Analysis]
57 Salvador R, Zhang A, Horai R, Caspi RR. Microbiota as Drivers and as Therapeutic Targets in Ocular and Tissue Specific Autoimmunity. Front Cell Dev Biol 2020;8:606751. [PMID: 33614621 DOI: 10.3389/fcell.2020.606751] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
58 Vosloo S, Huo L, Anderson CL, Dai Z, Sevillano M, Pinto A. Evaluating de Novo Assembly and Binning Strategies for Time Series Drinking Water Metagenomes. Microbiol Spectr 2021;:e0143421. [PMID: 34730411 DOI: 10.1128/Spectrum.01434-21] [Reference Citation Analysis]
59 Tan SM, Yung PYM, Hutchinson PE, Xie C, Teo GH, Ismail MH, Drautz-Moses DI, Little PFR, Williams RBH, Cohen Y. Primer-free FISH probes from metagenomics/metatranscriptomics data permit the study of uncharacterised taxa in complex microbial communities. NPJ Biofilms Microbiomes 2019;5:17. [PMID: 31263569 DOI: 10.1038/s41522-019-0090-9] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
60 Casimiro-Soriguer CS, Loucera C, Perez Florido J, López-López D, Dopazo J. Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples. Biol Direct 2019;14:15. [PMID: 31429791 DOI: 10.1186/s13062-019-0246-9] [Cited by in Crossref: 10] [Cited by in F6Publishing: 9] [Article Influence: 3.3] [Reference Citation Analysis]
61 Kayani MUR, Huang W, Feng R, Chen L. Genome-resolved metagenomics using environmental and clinical samples. Brief Bioinform 2021:bbab030. [PMID: 33758906 DOI: 10.1093/bib/bbab030] [Reference Citation Analysis]
62 Yu X, Zhou J, Song W, Xu M, He Q, Peng Y, Tian Y, Wang C, Shu L, Wang S, Yan Q, Liu J, Tu Q, He Z. SCycDB: A curated functional gene database for metagenomic profiling of sulphur cycling pathways. Mol Ecol Resour 2021;21:924-40. [DOI: 10.1111/1755-0998.13306] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
63 Shen J, McFarland AG, Young VB, Hayden MK, Hartmann EM. Toward Accurate and Robust Environmental Surveillance Using Metagenomics. Front Genet 2021;12:600111. [PMID: 33747038 DOI: 10.3389/fgene.2021.600111] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
64 Moreno I, Garcia-Grau I, Bau D, Perez-Villaroya D, Gonzalez-Monfort M, Vilella F, Romero R, Simón C. The first glimpse of the endometrial microbiota in early pregnancy. Am J Obstet Gynecol 2020;222:296-305. [PMID: 32057732 DOI: 10.1016/j.ajog.2020.01.031] [Cited by in Crossref: 16] [Cited by in F6Publishing: 16] [Article Influence: 8.0] [Reference Citation Analysis]
65 Gao B, Chi L, Zhu Y, Shi X, Tu P, Li B, Yin J, Gao N, Shen W, Schnabl B. An Introduction to Next Generation Sequencing Bioinformatic Analysis in Gut Microbiome Studies. Biomolecules 2021;11:530. [PMID: 33918473 DOI: 10.3390/biom11040530] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
66 Schimmel P, Kleinjans L, Bongers RS, Knol J, Belzer C. Breast milk urea as a nitrogen source for urease positive Bifidobacterium infantis. FEMS Microbiol Ecol 2021;97:fiab019. [PMID: 33538807 DOI: 10.1093/femsec/fiab019] [Reference Citation Analysis]
67 Walsh AM, Macori G, Kilcawley KN, Cotter PD. Meta-analysis of cheese microbiomes highlights contributions to multiple aspects of quality. Nat Food 2020;1:500-10. [DOI: 10.1038/s43016-020-0129-3] [Cited by in Crossref: 9] [Cited by in F6Publishing: 2] [Article Influence: 4.5] [Reference Citation Analysis]
68 Janssen K, Low SL, Wang Y, Mu QY, Bierbaum G, Gee CT. Elucidating biofilm diversity on water lily leaves through 16S rRNA amplicon analysis: Comparison of four DNA extraction kits. Appl Plant Sci 2021;9:e11444. [PMID: 34504737 DOI: 10.1002/aps3.11444] [Reference Citation Analysis]
69 Martín-Gómez MT. Taking a look on fungi in cystic fibrosis: More questions than answers. Rev Iberoam Micol 2020;37:17-23. [PMID: 31928888 DOI: 10.1016/j.riam.2019.10.004] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
70 Nazeen S, Yu YW, Berger B. Carnelian uncovers hidden functional patterns across diverse study populations from whole metagenome sequencing reads. Genome Biol 2020;21:47. [PMID: 32093762 DOI: 10.1186/s13059-020-1933-7] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
71 Mishima Y, Ishihara S. Molecular Mechanisms of Microbiota-Mediated Pathology in Irritable Bowel Syndrome. Int J Mol Sci. 2020;21. [PMID: 33212919 DOI: 10.3390/ijms21228664] [Cited by in Crossref: 5] [Cited by in F6Publishing: 8] [Article Influence: 2.5] [Reference Citation Analysis]
72 Boolchandani M, D'Souza AW, Dantas G. Sequencing-based methods and resources to study antimicrobial resistance. Nat Rev Genet 2019;20:356-70. [PMID: 30886350 DOI: 10.1038/s41576-019-0108-4] [Cited by in Crossref: 81] [Cited by in F6Publishing: 81] [Article Influence: 27.0] [Reference Citation Analysis]
73 Varricchi G, Poto R, Ianiro G, Punziano A, Marone G, Gasbarrini A, Spadaro G. Gut Microbiome and Common Variable Immunodeficiency: Few Certainties and Many Outstanding Questions. Front Immunol 2021;12:712915. [PMID: 34408753 DOI: 10.3389/fimmu.2021.712915] [Reference Citation Analysis]
74 Pereira-Marques J, Hout A, Ferreira RM, Weber M, Pinto-Ribeiro I, van Doorn LJ, Knetsch CW, Figueiredo C. Impact of Host DNA and Sequencing Depth on the Taxonomic Resolution of Whole Metagenome Sequencing for Microbiome Analysis. Front Microbiol 2019;10:1277. [PMID: 31244801 DOI: 10.3389/fmicb.2019.01277] [Cited by in Crossref: 42] [Cited by in F6Publishing: 34] [Article Influence: 14.0] [Reference Citation Analysis]
75 Wang T, Yang N, Liang C, Xu H, An Y, Xiao S, Zheng M, Liu L, Wang G, Nie L. Detecting Protein-Protein Interaction Based on Protein Fragment Complementation Assay. Curr Protein Pept Sci 2020;21:598-610. [PMID: 32053071 DOI: 10.2174/1389203721666200213102829] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
76 Albanese D, Coleine C, Rota-Stabelli O, Onofri S, Tringe SG, Stajich JE, Selbmann L, Donati C. Pre-Cambrian roots of novel Antarctic cryptoendolithic bacterial lineages. Microbiome 2021;9:63. [PMID: 33741058 DOI: 10.1186/s40168-021-01021-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
77 Chiara M, D'Erchia AM, Gissi C, Manzari C, Parisi A, Resta N, Zambelli F, Picardi E, Pavesi G, Horner DS, Pesole G. Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities. Brief Bioinform 2021;22:616-30. [PMID: 33279989 DOI: 10.1093/bib/bbaa297] [Cited by in Crossref: 14] [Cited by in F6Publishing: 13] [Article Influence: 14.0] [Reference Citation Analysis]
78 Hou Q, Wang Y, Cai W, Ni H, Zhao H, Zhang Z, Liu Z, Liu J, Zhong J, Guo Z. Metagenomic and physicochemical analyses reveal microbial community and functional differences between three types of low-temperature Daqu. Food Research International 2022;156:111167. [DOI: 10.1016/j.foodres.2022.111167] [Reference Citation Analysis]
79 Zhou Y, Liu M, Yang J. Recovering metagenome-assembled genomes from shotgun metagenomic sequencing data: methods, applications, challenges, and opportunities. Microbiological Research 2022. [DOI: 10.1016/j.micres.2022.127023] [Reference Citation Analysis]
80 Dror B, Jurkevitch E, Cytryn E. State-of-the-art methodologies to identify antimicrobial secondary metabolites in soil bacterial communities-A review. Soil Biology and Biochemistry 2020;147:107838. [DOI: 10.1016/j.soilbio.2020.107838] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 4.5] [Reference Citation Analysis]
81 Jing Y, Yuan Y, Monson M, Wang P, Mu F, Zhang Q, Na W, Zhang K, Wang Y, Leng L, Li Y, Luan P, Wang N, Guo R, Lamont SJ, Li H, Yuan H. Multi-Omics Association Reveals the Effects of Intestinal Microbiome–Host Interactions on Fat Deposition in Broilers. Front Microbiol 2022;12:815538. [DOI: 10.3389/fmicb.2021.815538] [Reference Citation Analysis]
82 Constantinides B, Chau KK, Quan TP, Rodger G, Andersson MI, Jeffery K, Lipworth S, Gweon HS, Peniket A, Pike G, Millo J, Byukusenge M, Holdaway M, Gibbons C, Mathers AJ, Crook DW, Peto TEA, Walker AS, Stoesser N. Genomic surveillance of Escherichia coli and Klebsiella spp. in hospital sink drains and patients. Microb Genom 2020;6. [PMID: 32553019 DOI: 10.1099/mgen.0.000391] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
83 Godlewska U, Brzoza P, Kwiecień K, Kwitniewski M, Cichy J. Metagenomic Studies in Inflammatory Skin Diseases. Curr Microbiol 2020;77:3201-12. [PMID: 32813091 DOI: 10.1007/s00284-020-02163-4] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
84 Neugent ML, Hulyalkar NV, Nguyen VH, Zimmern PE, De Nisco NJ. Advances in Understanding the Human Urinary Microbiome and Its Potential Role in Urinary Tract Infection. mBio 2020;11:e00218-20. [PMID: 32345639 DOI: 10.1128/mBio.00218-20] [Cited by in Crossref: 26] [Cited by in F6Publishing: 13] [Article Influence: 13.0] [Reference Citation Analysis]
85 Tedersoo L, Bahram M, Zinger L, Nilsson RH, Kennedy PG, Yang T, Anslan S, Mikryukov V. Best practices in metabarcoding of fungi: From experimental design to results. Mol Ecol 2022. [PMID: 35395127 DOI: 10.1111/mec.16460] [Reference Citation Analysis]
86 de Albuquerque GE, Moda BS, Serpa MS, Branco GP, Defelicibus A, Takenaka IKTM, de Amorim MG, Miola EC, Martins VCA, Torres KL, Bezerra SM, Claro LCL, Pelosof AG, Sztokfisz CZ, Abrantes LLS, Coimbra FJF, Kowalski LP, Alves FA, Zequi SC, Udekwu KI, Silva IT, Nunes DN, Bartelli TF, Dias-neto E. Evaluation of Bacteria and Fungi DNA Abundance in Human Tissues. Genes 2022;13:237. [DOI: 10.3390/genes13020237] [Reference Citation Analysis]
87 Pienkowska K, Wiehlmann L, Tümmler B. Airway microbial metagenomics. Microbes Infect 2018;20:536-42. [PMID: 29287982 DOI: 10.1016/j.micinf.2017.12.002] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 0.8] [Reference Citation Analysis]
88 Constantinou A, Kanti V, Polak-Witka K, Blume-Peytavi U, Spyrou GM, Vogt A. The Potential Relevance of the Microbiome to Hair Physiology and Regeneration: The Emerging Role of Metagenomics. Biomedicines 2021;9:236. [PMID: 33652789 DOI: 10.3390/biomedicines9030236] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
89 Enagbonma BJ, Babalola OO. Unveiling Plant-Beneficial Function as Seen in Bacteria Genes from Termite Mound Soil. J Soil Sci Plant Nutr 2020;20:421-30. [DOI: 10.1007/s42729-019-00124-w] [Cited by in Crossref: 9] [Cited by in F6Publishing: 2] [Article Influence: 4.5] [Reference Citation Analysis]
90 Furey TS, Sethupathy P, Sheikh SZ. Redefining the IBDs using genome-scale molecular phenotyping. Nat Rev Gastroenterol Hepatol. 2019;16:296-311. [PMID: 30787446 DOI: 10.1038/s41575-019-0118-x] [Cited by in Crossref: 24] [Cited by in F6Publishing: 21] [Article Influence: 8.0] [Reference Citation Analysis]
91 Bourke CD, Evans C. Cotrimoxazole Prophylaxis Selects for Antimicrobial Resistance in Human Immunodeficiency Virus-Exposed, Uninfected Infants. Clin Infect Dis 2020;71:2869-71. [PMID: 31832637 DOI: 10.1093/cid/ciz1193] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
92 Walsh AM, Crispie F, O'Sullivan O, Finnegan L, Claesson MJ, Cotter PD. Species classifier choice is a key consideration when analysing low-complexity food microbiome data. Microbiome 2018;6:50. [PMID: 29554948 DOI: 10.1186/s40168-018-0437-0] [Cited by in Crossref: 34] [Cited by in F6Publishing: 27] [Article Influence: 8.5] [Reference Citation Analysis]
93 Chen IA, Chu K, Palaniappan K, Pillay M, Ratner A, Huang J, Huntemann M, Varghese N, White JR, Seshadri R, Smirnova T, Kirton E, Jungbluth SP, Woyke T, Eloe-Fadrosh EA, Ivanova NN, Kyrpides NC. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res 2019;47:D666-77. [PMID: 30289528 DOI: 10.1093/nar/gky901] [Cited by in Crossref: 435] [Cited by in F6Publishing: 330] [Article Influence: 217.5] [Reference Citation Analysis]
94 LaPierre N, Alser M, Eskin E, Koslicki D, Mangul S. Metalign: efficient alignment-based metagenomic profiling via containment min hash. Genome Biol 2020;21:242. [PMID: 32912225 DOI: 10.1186/s13059-020-02159-0] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
95 Choudhary M, Jat HS, Datta A, Sharma PC, Rajashekar B, Jat ML. Topsoil Bacterial Community Changes and Nutrient Dynamics Under Cereal Based Climate-Smart Agri-Food Systems. Front Microbiol 2020;11:1812. [PMID: 32849419 DOI: 10.3389/fmicb.2020.01812] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
96 Pratt M, Forbes JD, Knox NC, Bernstein CN, Van Domselaar G. Microbiome-Mediated Immune Signaling in Inflammatory Bowel Disease and Colorectal Cancer: Support From Meta-omics Data. Front Cell Dev Biol 2021;9:716604. [PMID: 34869308 DOI: 10.3389/fcell.2021.716604] [Reference Citation Analysis]
97 Walker AW. A Lot on Your Plate? Well-to-Well Contamination as an Additional Confounder in Microbiome Sequence Analyses. mSystems 2019;4:e00362-19. [PMID: 31239398 DOI: 10.1128/mSystems.00362-19] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
98 Peimbert M, Alcaraz LD. Where environmental microbiome meets its host: subway and passenger microbiome relationships. Mol Ecol 2022. [PMID: 35318755 DOI: 10.1111/mec.16440] [Reference Citation Analysis]
99 Nisrina L, Effendi Y, Pancoro A. Revealing the role of Plant Growth Promoting Rhizobacteria in suppressive soils against Fusarium oxysporum f.sp. cubense based on metagenomic analysis. Heliyon 2021;7:e07636. [PMID: 34401567 DOI: 10.1016/j.heliyon.2021.e07636] [Reference Citation Analysis]
100 Forster SC, Kumar N, Anonye BO, Almeida A, Viciani E, Stares MD, Dunn M, Mkandawire TT, Zhu A, Shao Y, Pike LJ, Louie T, Browne HP, Mitchell AL, Neville BA, Finn RD, Lawley TD. A human gut bacterial genome and culture collection for improved metagenomic analyses. Nat Biotechnol 2019;37:186-92. [PMID: 30718869 DOI: 10.1038/s41587-018-0009-7] [Cited by in Crossref: 190] [Cited by in F6Publishing: 135] [Article Influence: 63.3] [Reference Citation Analysis]
101 Xing Z, Zhang Y, Li M, Guo C, Mi S. RBUD: A New Functional Potential Analysis Approach for Whole Microbial Genome Shotgun Sequencing. Microorganisms 2020;8:E1563. [PMID: 33050530 DOI: 10.3390/microorganisms8101563] [Reference Citation Analysis]
102 Guo J, Bolduc B, Zayed AA, Varsani A, Dominguez-Huerta G, Delmont TO, Pratama AA, Gazitúa MC, Vik D, Sullivan MB, Roux S. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome 2021;9:37. [PMID: 33522966 DOI: 10.1186/s40168-020-00990-y] [Cited by in Crossref: 20] [Cited by in F6Publishing: 14] [Article Influence: 20.0] [Reference Citation Analysis]
103 López-mondéjar R, Algora C, Baldrian P. Lignocellulolytic systems of soil bacteria: A vast and diverse toolbox for biotechnological conversion processes. Biotechnology Advances 2019;37:107374. [DOI: 10.1016/j.biotechadv.2019.03.013] [Cited by in Crossref: 27] [Cited by in F6Publishing: 19] [Article Influence: 9.0] [Reference Citation Analysis]
104 Liu J, Mu W, Shi M, Zhao Q, Kong W, Xie H, Shi L. The Species Identification in Traditional Herbal Patent Medicine, Wuhu San, Based on Shotgun Metabarcoding. Front Pharmacol 2021;12:607200. [PMID: 33664667 DOI: 10.3389/fphar.2021.607200] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
105 Zhou Y, Coventry DR, Gupta VVSR, Fuentes D, Merchant A, Kaiser BN, Li J, Wei Y, Liu H, Wang Y, Gan S, Denton MD. The preceding root system drives the composition and function of the rhizosphere microbiome. Genome Biol 2020;21:89. [PMID: 32252812 DOI: 10.1186/s13059-020-01999-0] [Cited by in Crossref: 15] [Cited by in F6Publishing: 7] [Article Influence: 7.5] [Reference Citation Analysis]
106 Crandall SG, Gold KM, Jiménez-Gasco MDM, Filgueiras CC, Willett DS. A multi-omics approach to solving problems in plant disease ecology. PLoS One 2020;15:e0237975. [PMID: 32960892 DOI: 10.1371/journal.pone.0237975] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
107 Duan H, He P, Shao L, Lü F. Functional genome-centric view of the CO-driven anaerobic microbiome. ISME J 2021;15:2906-19. [PMID: 33911204 DOI: 10.1038/s41396-021-00983-1] [Reference Citation Analysis]
108 Abbas AA, Young JC, Clarke EL, Diamond JM, Imai I, Haas AR, Cantu E, Lederer DJ, Meyer K, Milewski RK, Olthoff KM, Shaked A, Christie JD, Bushman FD, Collman RG. Bidirectional transfer of Anelloviridae lineages between graft and host during lung transplantation. Am J Transplant 2019;19:1086-97. [PMID: 30203917 DOI: 10.1111/ajt.15116] [Cited by in Crossref: 15] [Cited by in F6Publishing: 15] [Article Influence: 3.8] [Reference Citation Analysis]
109 Vázquez-castellanos JF, Biclot A, Vrancken G, Huys GR, Raes J. Design of synthetic microbial consortia for gut microbiota modulation. Current Opinion in Pharmacology 2019;49:52-9. [DOI: 10.1016/j.coph.2019.07.005] [Cited by in Crossref: 13] [Cited by in F6Publishing: 12] [Article Influence: 4.3] [Reference Citation Analysis]
110 Cattonaro F, Spadotto A, Radovic S, Marroni F. Do you cov me? Effect of coverage reduction on metagenome shotgun sequencing studies. F1000Res 2018;7:1767. [PMID: 32185014 DOI: 10.12688/f1000research.16804.4] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
111 Zhang Y, Thompson KN, Huttenhower C, Franzosa EA. Statistical approaches for differential expression analysis in metatranscriptomics. Bioinformatics 2021;37:i34-41. [PMID: 34252963 DOI: 10.1093/bioinformatics/btab327] [Reference Citation Analysis]
112 Piombo E, Abdelfattah A, Droby S, Wisniewski M, Spadaro D, Schena L. Metagenomics Approaches for the Detection and Surveillance of Emerging and Recurrent Plant Pathogens. Microorganisms 2021;9:188. [PMID: 33467169 DOI: 10.3390/microorganisms9010188] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
113 Eetemadi A, Rai N, Pereira BMP, Kim M, Schmitz H, Tagkopoulos I. The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health. Front Microbiol 2020;11:393. [PMID: 32318028 DOI: 10.3389/fmicb.2020.00393] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 5.5] [Reference Citation Analysis]
114 Li Y, He XZ, Li MH, Li B, Yang MJ, Xie Y, Zhang Y, Ma XJ. Comparison of third-generation sequencing approaches to identify viral pathogens under public health emergency conditions. Virus Genes 2020;56:288-97. [PMID: 32193781 DOI: 10.1007/s11262-020-01746-4] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
115 Mreyoud Y, Song M, Lim J, Ahn T. MegaD: Deep Learning for Rapid and Accurate Disease Status Prediction of Metagenomic Samples. Life 2022;12:669. [DOI: 10.3390/life12050669] [Reference Citation Analysis]
116 Dhungel E, Mreyoud Y, Gwak HJ, Rajeh A, Rho M, Ahn TH. MegaR: an interactive R package for rapid sample classification and phenotype prediction using metagenome profiles and machine learning. BMC Bioinformatics 2021;22:25. [PMID: 33461494 DOI: 10.1186/s12859-020-03933-4] [Reference Citation Analysis]
117 Tingley JP, Low KE, Xing X, Abbott DW. Combined whole cell wall analysis and streamlined in silico carbohydrate-active enzyme discovery to improve biocatalytic conversion of agricultural crop residues. Biotechnol Biofuels 2021;14:16. [PMID: 33422151 DOI: 10.1186/s13068-020-01869-8] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
118 Segal JP, Mullish BH, Quraishi MN, Acharjee A, Williams HRT, Iqbal T, Hart AL, Marchesi JR. The application of omics techniques to understand the role of the gut microbiota in inflammatory bowel disease. Therap Adv Gastroenterol 2019;12:1756284818822250. [PMID: 30719076 DOI: 10.1177/1756284818822250] [Cited by in Crossref: 26] [Cited by in F6Publishing: 24] [Article Influence: 8.7] [Reference Citation Analysis]
119 Da Silva K, Pons N, Berland M, Plaza Oñate F, Almeida M, Peterlongo P. StrainFLAIR: strain-level profiling of metagenomic samples using variation graphs. PeerJ 2021;9:e11884. [PMID: 34513324 DOI: 10.7717/peerj.11884] [Reference Citation Analysis]
120 Picardo SL, Coburn B, Hansen AR. The microbiome and cancer for clinicians. Crit Rev Oncol Hematol. 2019;141:1-12. [PMID: 31202124 DOI: 10.1016/j.critrevonc.2019.06.004] [Cited by in Crossref: 33] [Cited by in F6Publishing: 27] [Article Influence: 11.0] [Reference Citation Analysis]
121 Latorre-Pérez A, Pascual J, Porcar M, Vilanova C. A lab in the field: applications of real-time, in situ metagenomic sequencing. Biol Methods Protoc 2020;5:bpaa016. [PMID: 33134552 DOI: 10.1093/biomethods/bpaa016] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
122 Farraj SA, El-Kafrawy SA, Kumosani TA, Yousef JM, Azhar EI. Evaluation of Extraction Methods for Clinical Metagenomic Assay. Microorganisms 2020;8:E1128. [PMID: 32727010 DOI: 10.3390/microorganisms8081128] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
123 de Abreu VAC, Perdigão J, Almeida S. Metagenomic Approaches to Analyze Antimicrobial Resistance: An Overview. Front Genet 2020;11:575592. [PMID: 33537056 DOI: 10.3389/fgene.2020.575592] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
124 Saati-Santamaría Z, Rivas R, Kolařik M, García-Fraile P. A New Perspective of Pseudomonas-Host Interactions: Distribution and Potential Ecological Functions of the Genus Pseudomonas within the Bark Beetle Holobiont. Biology (Basel) 2021;10:164. [PMID: 33669823 DOI: 10.3390/biology10020164] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
125 He T, Jin L, Li X. On the triad of air PM pollution, pathogenic bioaerosols, and lower respiratory infection. Environ Geochem Health 2021. [PMID: 34236582 DOI: 10.1007/s10653-021-01025-7] [Reference Citation Analysis]
126 Lam T, Yang J, Lai S, Liang S, Wu S. Meta-proteomics analysis of microbial ecosystem during the anaerobic digestion of chicken manure in biogas production farm. Bioresource Technology Reports 2021;13:100643. [DOI: 10.1016/j.biteb.2021.100643] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
127 Abraham BS, Caglayan D, Carrillo NV, Chapman MC, Hagan CT, Hansen ST, Jeanty RO, Klimczak AA, Klingler MJ, Kutcher TP, Levy SH, Millard-Bruzos AA, Moore TB, Prentice DJ, Prescott ME, Roehm R, Rose JA, Yin M, Hyodo A, Lail K, Daum C, Clum A, Copeland A, Seshadri R, Del Rio TG, Eloe-Fadrosh EA, Benskin JB. Shotgun metagenomic analysis of microbial communities from the Loxahatchee nature preserve in the Florida Everglades. Environ Microbiome 2020;15:2. [PMID: 33902723 DOI: 10.1186/s40793-019-0352-4] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 2.5] [Reference Citation Analysis]
128 Ong CT, Boe-hansen G, Ross EM, Blackall PJ, Turni C, Hayes BJ, Tabor AE, Ning K. Evaluation of Host Depletion and Extraction Methods for Shotgun Metagenomic Analysis of Bovine Vaginal Samples. Microbiol Spectr. [DOI: 10.1128/spectrum.00412-21] [Reference Citation Analysis]
129 Uritskiy G, DiRuggiero J. Applying Genome-Resolved Metagenomics to Deconvolute the Halophilic Microbiome. Genes (Basel) 2019;10:E220. [PMID: 30875864 DOI: 10.3390/genes10030220] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 3.7] [Reference Citation Analysis]
130 Quince C, Walker AW, Simpson JT, Loman NJ, Segata N. Corrigendum: Shotgun metagenomics, from sampling to analysis. Nat Biotechnol 2017;35:1211. [PMID: 29220029 DOI: 10.1038/nbt1217-1211b] [Cited by in Crossref: 17] [Cited by in F6Publishing: 16] [Article Influence: 3.4] [Reference Citation Analysis]
131 Liu Y, Liu B, Liu C, Hu Y, Liu C, Li X, Li X, Zhang X, Irwin DM, Wu Z, Chen Z, Jin Q, Zhang S. Differences in the gut microbiomes of dogs and wolves: roles of antibiotics and starch. BMC Vet Res 2021;17:112. [PMID: 33676490 DOI: 10.1186/s12917-021-02815-y] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
132 Smith SD, Choi J, Ricker N, Yang F, Hinsa-Leasure S, Soupir ML, Allen HK, Howe A. Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM): a method for detection of antimicrobial resistance in environmental samples. Commun Biol 2022;5:216. [PMID: 35301418 DOI: 10.1038/s42003-022-03155-9] [Reference Citation Analysis]
133 Ferravante C, Memoli D, Palumbo D, Ciaramella P, Di Loria A, D'Agostino Y, Nassa G, Rizzo F, Tarallo R, Weisz A, Giurato G. HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities): a specific and comprehensive pipeline for metagenomic shotgun sequencing data analysis. BMC Bioinformatics 2021;22:106. [PMID: 34225648 DOI: 10.1186/s12859-021-04004-y] [Reference Citation Analysis]
134 Dada N, Jupatanakul N, Minard G, Short SM, Akorli J, Villegas LM. Considerations for mosquito microbiome research from the Mosquito Microbiome Consortium. Microbiome 2021;9:36. [PMID: 33522965 DOI: 10.1186/s40168-020-00987-7] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
135 Alamri A. Diversity of Microbial Signatures in Asthmatic Airways. Int J Gen Med 2021;14:1367-78. [PMID: 33889017 DOI: 10.2147/IJGM.S304339] [Reference Citation Analysis]
136 Ianiro G, Rossi E, Thomas AM, Schinzari G, Masucci L, Quaranta G, Settanni CR, Lopetuso LR, Armanini F, Blanco-Miguez A, Asnicar F, Consolandi C, Iacovelli R, Sanguinetti M, Tortora G, Gasbarrini A, Segata N, Cammarota G. Faecal microbiota transplantation for the treatment of diarrhoea induced by tyrosine-kinase inhibitors in patients with metastatic renal cell carcinoma. Nat Commun 2020;11:4333. [PMID: 32859933 DOI: 10.1038/s41467-020-18127-y] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 8.0] [Reference Citation Analysis]
137 Bouranis JA, Beaver LM, Ho E. Metabolic Fate of Dietary Glucosinolates and Their Metabolites: A Role for the Microbiome. Front Nutr 2021;8:748433. [PMID: 34631775 DOI: 10.3389/fnut.2021.748433] [Reference Citation Analysis]
138 Duarte ASR, Stärk KDC, Munk P, Leekitcharoenphon P, Bossers A, Luiken R, Sarrazin S, Lukjancenko O, Pamp SJ, Bortolaia V, Nissen JN, Kirstahler P, Van Gompel L, Poulsen CS, Kaas RS, Hellmér M, Hansen RB, Gomez VM, Hald T. Addressing Learning Needs on the Use of Metagenomics in Antimicrobial Resistance Surveillance. Front Public Health 2020;8:38. [PMID: 32158739 DOI: 10.3389/fpubh.2020.00038] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
139 Sencio V, Machado MG, Trottein F. The lung-gut axis during viral respiratory infections: the impact of gut dysbiosis on secondary disease outcomes. Mucosal Immunol 2021;14:296-304. [PMID: 33500564 DOI: 10.1038/s41385-020-00361-8] [Cited by in Crossref: 15] [Cited by in F6Publishing: 16] [Article Influence: 15.0] [Reference Citation Analysis]
140 Biderre-Petit C, Taib N, Gardon H, Hochart C, Debroas D. New insights into the pelagic microorganisms involved in the methane cycle in the meromictic Lake Pavin through metagenomics. FEMS Microbiol Ecol 2019;95. [PMID: 30203066 DOI: 10.1093/femsec/fiy183] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 3.5] [Reference Citation Analysis]
141 Barton Pai A, Garba A, Neumann P, Prokopienko AJ, Costello G, Dean MC, Narsipur S. Quantification of Lipoteichoic Acid in Hemodialysis Patients With Central Venous Catheters. Front Med (Lausanne) 2018;5:308. [PMID: 30456212 DOI: 10.3389/fmed.2018.00308] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
142 Wong J, Manoil D, Näsman P, Belibasakis GN, Neelakantan P. Microbiological Aspects of Root Canal Infections and Disinfection Strategies: An Update Review on the Current Knowledge and Challenges. Front Oral Health 2021;2:672887. [PMID: 35048015 DOI: 10.3389/froh.2021.672887] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
143 Kauter A, Epping L, Semmler T, Antao EM, Kannapin D, Stoeckle SD, Gehlen H, Lübke-Becker A, Günther S, Wieler LH, Walther B. The gut microbiome of horses: current research on equine enteral microbiota and future perspectives. Anim Microbiome 2019;1:14. [PMID: 33499951 DOI: 10.1186/s42523-019-0013-3] [Cited by in Crossref: 16] [Cited by in F6Publishing: 10] [Article Influence: 5.3] [Reference Citation Analysis]
144 Thorn CE, Bergesch C, Joyce A, Sambrano G, McDonnell K, Brennan F, Heyer R, Benndorf D, Abram F. A robust, cost-effective method for DNA, RNA and protein co-extraction from soil, other complex microbiomes and pure cultures. Mol Ecol Resour 2019;19:439-55. [PMID: 30565880 DOI: 10.1111/1755-0998.12979] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 2.3] [Reference Citation Analysis]
145 Pereira-Flores E, Glöckner FO, Fernandez-Guerra A. Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data. BMC Bioinformatics 2019;20:453. [PMID: 31488068 DOI: 10.1186/s12859-019-3031-y] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
146 Lewis S, Nash A, Li Q, Ahn TH. Comparison of 16S and whole genome dog microbiomes using machine learning. BioData Min 2021;14:41. [PMID: 34419136 DOI: 10.1186/s13040-021-00270-x] [Reference Citation Analysis]
147 Su M, Satola SW, Read TD. Genome-Based Prediction of Bacterial Antibiotic Resistance. J Clin Microbiol 2019;57:e01405-18. [PMID: 30381421 DOI: 10.1128/JCM.01405-18] [Cited by in Crossref: 76] [Cited by in F6Publishing: 52] [Article Influence: 25.3] [Reference Citation Analysis]
148 Alneberg J, Karlsson CMG, Divne AM, Bergin C, Homa F, Lindh MV, Hugerth LW, Ettema TJG, Bertilsson S, Andersson AF, Pinhassi J. Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomes. Microbiome 2018;6:173. [PMID: 30266101 DOI: 10.1186/s40168-018-0550-0] [Cited by in Crossref: 36] [Cited by in F6Publishing: 28] [Article Influence: 9.0] [Reference Citation Analysis]
149 Huang Q, Fang Q, Hu Z. A P4 Medicine Perspective of Gut Microbiota and Prediabetes: Systems Analysis and Personalized Intervention. J Transl Int Med 2020;8:119-30. [PMID: 33062587 DOI: 10.2478/jtim-2020-0020] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
150 Vervier K, Mahé P, Vert JP. MetaVW: Large-Scale Machine Learning for Metagenomics Sequence Classification. Methods Mol Biol 2018;1807:9-20. [PMID: 30030800 DOI: 10.1007/978-1-4939-8561-6_2] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 1.3] [Reference Citation Analysis]
151 Segata N. On the Road to Strain-Resolved Comparative Metagenomics. mSystems 2018;3:e00190-17. [PMID: 29556534 DOI: 10.1128/mSystems.00190-17] [Cited by in Crossref: 62] [Cited by in F6Publishing: 31] [Article Influence: 15.5] [Reference Citation Analysis]
152 Krehenwinkel H, Pomerantz A, Prost S. Genetic Biomonitoring and Biodiversity Assessment Using Portable Sequencing Technologies: Current Uses and Future Directions. Genes (Basel) 2019;10:E858. [PMID: 31671909 DOI: 10.3390/genes10110858] [Cited by in Crossref: 32] [Cited by in F6Publishing: 24] [Article Influence: 10.7] [Reference Citation Analysis]
153 Breitwieser FP, Baker DN, Salzberg SL. KrakenUniq: confident and fast metagenomics classification using unique k-mer counts. Genome Biol 2018;19:198. [PMID: 30445993 DOI: 10.1186/s13059-018-1568-0] [Cited by in Crossref: 108] [Cited by in F6Publishing: 72] [Article Influence: 27.0] [Reference Citation Analysis]
154 Mthethwa NP, Amoah ID, Reddy P, Bux F, Kumari S. A review on application of next-generation sequencing methods for profiling of protozoan parasites in water: Current methodologies, challenges, and perspectives. J Microbiol Methods 2021;187:106269. [PMID: 34129906 DOI: 10.1016/j.mimet.2021.106269] [Reference Citation Analysis]
155 King MD, Lacey RE, Pak H, Fearing A, Ramos G, Baig T, Smith B, Koustova A. Assays and enumeration of bioaerosols-traditional approaches to modern practices. Aerosol Science and Technology 2020;54:611-33. [DOI: 10.1080/02786826.2020.1723789] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 4.5] [Reference Citation Analysis]
156 Morrow JD, Castaldi PJ, Chase RP, Yun JH, Lee S, Liu YY, Hersh CP. Peripheral blood microbial signatures in current and former smokers. Sci Rep 2021;11:19875. [PMID: 34615932 DOI: 10.1038/s41598-021-99238-4] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
157 Roy D, Tomo S, Purohit P, Setia P. Microbiome in Death and Beyond: Current Vistas and Future Trends. Front Ecol Evol 2021;9:630397. [DOI: 10.3389/fevo.2021.630397] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
158 Miller IJ, Rees ER, Ross J, Miller I, Baxa J, Lopera J, Kerby RL, Rey FE, Kwan JC. Autometa: automated extraction of microbial genomes from individual shotgun metagenomes. Nucleic Acids Res 2019;47:e57. [PMID: 30838416 DOI: 10.1093/nar/gkz148] [Cited by in Crossref: 22] [Cited by in F6Publishing: 18] [Article Influence: 7.3] [Reference Citation Analysis]
159 Zhong XZ, Li XX, Zeng Y, Wang SP, Sun ZY, Tang YQ. Dynamic change of bacterial community during dairy manure composting process revealed by high-throughput sequencing and advanced bioinformatics tools. Bioresour Technol 2020;306:123091. [PMID: 32169511 DOI: 10.1016/j.biortech.2020.123091] [Cited by in Crossref: 20] [Cited by in F6Publishing: 14] [Article Influence: 10.0] [Reference Citation Analysis]
160 Gweon HS, Shaw LP, Swann J, De Maio N, AbuOun M, Niehus R, Hubbard ATM, Bowes MJ, Bailey MJ, Peto TEA, Hoosdally SJ, Walker AS, Sebra RP, Crook DW, Anjum MF, Read DS, Stoesser N; REHAB consortium. The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples. Environ Microbiome 2019;14:7. [PMID: 33902704 DOI: 10.1186/s40793-019-0347-1] [Cited by in Crossref: 22] [Cited by in F6Publishing: 8] [Article Influence: 7.3] [Reference Citation Analysis]
161 Yulandi A, Suwanto A, Waturangi DE, Wahyudi AT. Shotgun metagenomic analysis reveals new insights into bacterial community profiles in tempeh. BMC Res Notes 2020;13:562. [PMID: 33308279 DOI: 10.1186/s13104-020-05406-6] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
162 Wang Q, Ye J, Fang D, Lv L, Wu W, Shi D, Li Y, Yang L, Bian X, Wu J, Jiang X, Wang K, Wang Q, Hodson MP, Thibaut LM, Ho JWK, Giannoulatou E, Li L. Multi-omic profiling reveals associations between the gut mucosal microbiome, the metabolome, and host DNA methylation associated gene expression in patients with colorectal cancer. BMC Microbiol 2020;20:83. [PMID: 32321427 DOI: 10.1186/s12866-020-01762-2] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 4.5] [Reference Citation Analysis]
163 Watson RL, de Koff EM, Bogaert D. Characterising the respiratory microbiome. Eur Respir J 2019;53:1801711. [PMID: 30487204 DOI: 10.1183/13993003.01711-2018] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 3.7] [Reference Citation Analysis]
164 Eze MO, Hose GC, George SC, Daniel R. Diversity and metagenome analysis of a hydrocarbon-degrading bacterial consortium from asphalt lakes located in Wietze, Germany. AMB Express 2021;11:89. [PMID: 34125309 DOI: 10.1186/s13568-021-01250-4] [Reference Citation Analysis]
165 Kigerl KA, Zane K, Adams K, Sullivan MB, Popovich PG. The spinal cord-gut-immune axis as a master regulator of health and neurological function after spinal cord injury. Exp Neurol. 2020;323:113085. [PMID: 31654639 DOI: 10.1016/j.expneurol.2019.113085] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 5.3] [Reference Citation Analysis]
166 Araos R, D'Agata EMC. The human microbiota and infection prevention. Infect Control Hosp Epidemiol 2019;40:585-9. [PMID: 30777586 DOI: 10.1017/ice.2019.28] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
167 Li D, Gao C, Zhang F, Yang R, Lan C, Ma Y, Wang J. Seven facts and five initiatives for gut microbiome research. Protein Cell. 2020;11:391-400. [PMID: 32172500 DOI: 10.1007/s13238-020-00697-8] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
168 Kaiser H, Kvist-Hansen A, Becker C, Wang X, McCauley BD, Krakauer M, Gørtz PM, Henningsen KMA, Zachariae C, Skov L, Hansen PR. Multiscale Biology of Cardiovascular Risk in Psoriasis: Protocol for a Case-Control Study. JMIR Res Protoc 2021;10:e28669. [PMID: 34581684 DOI: 10.2196/28669] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
169 Eng A, Verster AJ, Borenstein E. MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline. BMC Bioinformatics 2020;21:471. [PMID: 33087062 DOI: 10.1186/s12859-020-03815-9] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
170 Nyholm L, Odriozola I, Martin Bideguren G, Aizpurua O, Alberdi A. Gut microbiota differences between paired intestinal wall and digesta samples in three small species of fish. PeerJ 2022;10:e12992. [DOI: 10.7717/peerj.12992] [Reference Citation Analysis]
171 Liu J, Shi M, Zhao Q, Kong W, Mu W, Xie H, Li Z, Li B, Shi L. Precise Species Detection in Traditional Herbal Patent Medicine, Qingguo Wan, Using Shotgun Metabarcoding. Front Pharmacol 2021;12:607210. [PMID: 33995010 DOI: 10.3389/fphar.2021.607210] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
172 Bokulich NA, Ziemski M, Robeson MS 2nd, Kaehler BD. Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods. Comput Struct Biotechnol J 2020;18:4048-62. [PMID: 33363701 DOI: 10.1016/j.csbj.2020.11.049] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 4.5] [Reference Citation Analysis]
173 Vuorio K, Mäki A, Salmi P, Aalto SL, Tiirola M. Consistency of Targeted Metatranscriptomics and Morphological Characterization of Phytoplankton Communities. Front Microbiol 2020;11:96. [PMID: 32117126 DOI: 10.3389/fmicb.2020.00096] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
174 Choi SC, Brown J, Gong M, Ge Y, Zadeh M, Li W, Croker BP, Michailidis G, Garrett TJ, Mohamadzadeh M, Morel L. Gut microbiota dysbiosis and altered tryptophan catabolism contribute to autoimmunity in lupus-susceptible mice. Sci Transl Med 2020;12:eaax2220. [PMID: 32641487 DOI: 10.1126/scitranslmed.aax2220] [Cited by in Crossref: 22] [Cited by in F6Publishing: 21] [Article Influence: 22.0] [Reference Citation Analysis]
175 Meng X, Zhou HY, Shen HH, Lufumpa E, Li XM, Guo B, Li BZ. Microbe-metabolite-host axis, two-way action in the pathogenesis and treatment of human autoimmunity. Autoimmun Rev 2019;18:455-75. [PMID: 30844549 DOI: 10.1016/j.autrev.2019.03.006] [Cited by in Crossref: 20] [Cited by in F6Publishing: 19] [Article Influence: 6.7] [Reference Citation Analysis]
176 Thiele-bruhn S, Schloter M, Wilke B, Beaudette LA, Martin-laurent F, Cheviron N, Mougin C, Römbke J. Identification of new microbial functional standards for soil quality assessment. SOIL 2020;6:17-34. [DOI: 10.5194/soil-6-17-2020] [Cited by in Crossref: 13] [Cited by in F6Publishing: 4] [Article Influence: 6.5] [Reference Citation Analysis]
177 Stratton CW, Schutzbank TE, Tang YW. Use of Metagenomic Next-Generation Sequencing in the Clinical Microbiology Laboratory: A Step Forward, but Not an End-All. J Mol Diagn 2021;23:1415-21. [PMID: 34756275 DOI: 10.1016/j.jmoldx.2021.09.003] [Reference Citation Analysis]
178 Mukherjee D, Chora ÂF, Mota MM. Microbiota, a Third Player in the Host-Plasmodium Affair. Trends Parasitol 2020;36:11-8. [PMID: 31787522 DOI: 10.1016/j.pt.2019.11.001] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 4.0] [Reference Citation Analysis]
179 Laborda-Illanes A, Sanchez-Alcoholado L, Dominguez-Recio ME, Jimenez-Rodriguez B, Lavado R, Comino-Méndez I, Alba E, Queipo-Ortuño MI. Breast and Gut Microbiota Action Mechanisms in Breast Cancer Pathogenesis and Treatment. Cancers (Basel) 2020;12:E2465. [PMID: 32878124 DOI: 10.3390/cancers12092465] [Cited by in Crossref: 16] [Cited by in F6Publishing: 16] [Article Influence: 8.0] [Reference Citation Analysis]
180 Pinto F, Tett A, Armanini F, Asnicar F, Boscaini A, Pasolli E, Zolfo M, Donati C, Salmaso N, Segata N. Draft Genome Sequences of Novel Pseudomonas, Flavobacterium, and Sediminibacterium [corrected] Strains from a Freshwater Ecosystem. Genome Announc 2018;6:e00009-18. [PMID: 29437085 DOI: 10.1128/genomeA.00009-18] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
181 Li M, Song G, Liu R, Huang X, Liu H. Inactivation and risk control of pathogenic microorganisms in municipal sludge treatment: A review. Front Environ Sci Eng 2022;16:70. [PMID: 34608423 DOI: 10.1007/s11783-021-1504-5] [Reference Citation Analysis]
182 Segata N. No bacteria found in healthy placentas. Nature 2019;572:317-8. [PMID: 31406307 DOI: 10.1038/d41586-019-02262-8] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 2.3] [Reference Citation Analysis]
183 Bost A, Martinson VG, Franzenburg S, Adair KL, Albasi A, Wells MT, Douglas AE. Functional variation in the gut microbiome of wild Drosophila populations. Mol Ecol 2018;27:2834-45. [DOI: 10.1111/mec.14728] [Cited by in Crossref: 25] [Cited by in F6Publishing: 19] [Article Influence: 6.3] [Reference Citation Analysis]
184 Cheng L, Kong L, Xia C, Zeng X, Wu Z, Guo Y, Pan D. Sources, Processing-Related Transformation, and Gut Axis Regulation of Conventional and Potential Prebiotics. J Agric Food Chem 2022. [PMID: 35389646 DOI: 10.1021/acs.jafc.2c00168] [Reference Citation Analysis]
185 McGhee JJ, Rawson N, Bailey BA, Fernandez-Guerra A, Sisk-Hackworth L, Kelley ST. Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics. PeerJ 2020;8:e8783. [PMID: 32231882 DOI: 10.7717/peerj.8783] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
186 Modha S, Robertson DL, Hughes J, Orton RJ. Quantifying and Cataloguing Unknown Sequences within Human Microbiomes. mSystems 2022;:e0146821. [PMID: 35258340 DOI: 10.1128/msystems.01468-21] [Reference Citation Analysis]
187 Banasiewicz J, Lisboa BB, da Costa PB, Schlindwein G, Venter SN, Steenkamp ET, Vargas LK, Passaglia LMP, Stępkowski T. Culture-independent assessment of the diazotrophic Bradyrhizobium communities in the Pampa and Atlantic Forest Biomes localities in southern Brazil. Syst Appl Microbiol 2021;44:126228. [PMID: 34265499 DOI: 10.1016/j.syapm.2021.126228] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
188 Sorensen JW, Zinke LA, Ter Horst AM, Santos-Medellín C, Schroeder A, Emerson JB. DNase Treatment Improves Viral Enrichment in Agricultural Soil Viromes. mSystems 2021;6:e0061421. [PMID: 34491084 DOI: 10.1128/mSystems.00614-21] [Reference Citation Analysis]
189 Gaulke CA, Schmeltzer ER, Dasenko M, Tyler BM, Vega Thurber R, Sharpton TJ. Evaluation of the Effects of Library Preparation Procedure and Sample Characteristics on the Accuracy of Metagenomic Profiles. mSystems 2021;6:e0044021. [PMID: 34636674 DOI: 10.1128/mSystems.00440-21] [Reference Citation Analysis]
190 Clarke EL, Taylor LJ, Zhao C, Connell A, Lee JJ, Fett B, Bushman FD, Bittinger K. Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments. Microbiome 2019;7:46. [PMID: 30902113 DOI: 10.1186/s40168-019-0658-x] [Cited by in Crossref: 44] [Cited by in F6Publishing: 36] [Article Influence: 14.7] [Reference Citation Analysis]
191 de Medeiros Azevedo T, Aburjaile FF, Ferreira-Neto JRC, Pandolfi V, Benko-Iseppon AM. The endophytome (plant-associated microbiome): methodological approaches, biological aspects, and biotech applications. World J Microbiol Biotechnol 2021;37:206. [PMID: 34708327 DOI: 10.1007/s11274-021-03168-2] [Reference Citation Analysis]
192 Day RL, Harper AJ, Woods RM, Davies OG, Heaney LM. Probiotics: current landscape and future horizons. Future Sci OA 2019;5:FSO391. [PMID: 31114711 DOI: 10.4155/fsoa-2019-0004] [Cited by in Crossref: 21] [Cited by in F6Publishing: 16] [Article Influence: 7.0] [Reference Citation Analysis]
193 Lyu Y, Su C, Verbrugghe A, Van de Wiele T, Martos Martinez-Caja A, Hesta M. Past, Present, and Future of Gastrointestinal Microbiota Research in Cats. Front Microbiol 2020;11:1661. [PMID: 32793152 DOI: 10.3389/fmicb.2020.01661] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 3.5] [Reference Citation Analysis]
194 Gardner PP, Watson RJ, Morgan XC, Draper JL, Finn RD, Morales SE, Stott MB. Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies. PeerJ 2019;7:e6160. [PMID: 30631651 DOI: 10.7717/peerj.6160] [Cited by in Crossref: 21] [Cited by in F6Publishing: 13] [Article Influence: 7.0] [Reference Citation Analysis]
195 Heymann CJF, Bard JM, Heymann MF, Heymann D, Bobin-Dubigeon C. The intratumoral microbiome: Characterization methods and functional impact. Cancer Lett 2021;522:63-79. [PMID: 34517085 DOI: 10.1016/j.canlet.2021.09.009] [Reference Citation Analysis]
196 Vasta V, Daghio M, Cappucci A, Buccioni A, Serra A, Viti C, Mele M. Invited review: Plant polyphenols and rumen microbiota responsible for fatty acid biohydrogenation, fiber digestion, and methane emission: Experimental evidence and methodological approaches. J Dairy Sci 2019;102:3781-804. [PMID: 30904293 DOI: 10.3168/jds.2018-14985] [Cited by in Crossref: 70] [Cited by in F6Publishing: 41] [Article Influence: 23.3] [Reference Citation Analysis]
197 Song E, Lee E, Nam Y. Progress of analytical tools and techniques for human gut microbiome research. J Microbiol 2018;56:693-705. [DOI: 10.1007/s12275-018-8238-5] [Cited by in Crossref: 27] [Cited by in F6Publishing: 23] [Article Influence: 6.8] [Reference Citation Analysis]
198 Zhang Y, Qi Y, Lo ECM, McGrath C, Mei ML, Dai R. Using next-generation sequencing to detect oral microbiome change following periodontal interventions: A systematic review. Oral Dis 2021;27:1073-89. [PMID: 32390250 DOI: 10.1111/odi.13405] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
199 Huang Y, Zhao X, Cui L, Huang S. Metagenomic and Metatranscriptomic Insight Into Oral Biofilms in Periodontitis and Related Systemic Diseases. Front Microbiol 2021;12:728585. [PMID: 34721325 DOI: 10.3389/fmicb.2021.728585] [Reference Citation Analysis]
200 Huang X, Fan Y, Lu T, Kang J, Pang X, Han B, Chen J. Composition and Metabolic Functions of the Microbiome in Fermented Grain during Light-Flavor Baijiu Fermentation. Microorganisms 2020;8:E1281. [PMID: 32842618 DOI: 10.3390/microorganisms8091281] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
201 [DOI: 10.1101/372474] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
202 Clavel T, Horz HP, Segata N, Vehreschild M. Next steps after 15 stimulating years of human gut microbiome research. Microb Biotechnol 2022;15:164-75. [PMID: 34818454 DOI: 10.1111/1751-7915.13970] [Reference Citation Analysis]
203 Fonseca M, Heider LC, Léger D, Mcclure JT, Rizzo D, Dufour S, Kelton DF, Renaud D, Barkema HW, Sanchez J. Canadian Dairy Network for Antimicrobial Stewardship and Resistance (CaDNetASR): An On-Farm Surveillance System. Front Vet Sci 2022;8:799622. [DOI: 10.3389/fvets.2021.799622] [Reference Citation Analysis]
204 Jia B, Han X, Kim KH, Jeon CO. Discovery and mining of enzymes from the human gut microbiome. Trends Biotechnol 2021:S0167-7799(21)00138-4. [PMID: 34304905 DOI: 10.1016/j.tibtech.2021.06.008] [Reference Citation Analysis]
205 Koutsoumanis K, Allende A, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Hilbert F, Lindqvist R, Nauta M, Peixe L, Ru G, Simmons M, Skandamis P, Suffredini E, Jenkins C, Malorny B, Ribeiro Duarte AS, Torpdahl M, da Silva Felício MT, Guerra B, Rossi M, Herman L; EFSA Panel on Biological Hazards (EFSA BIOHAZ Panel). Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food-borne microorganisms. EFSA J 2019;17:e05898. [PMID: 32626197 DOI: 10.2903/j.efsa.2019.5898] [Cited by in Crossref: 19] [Cited by in F6Publishing: 21] [Article Influence: 6.3] [Reference Citation Analysis]
206 Slizovskiy IB, Mukherjee K, Dean CJ, Boucher C, Noyes NR. Mobilization of Antibiotic Resistance: Are Current Approaches for Colocalizing Resistomes and Mobilomes Useful? Front Microbiol 2020;11:1376. [PMID: 32695079 DOI: 10.3389/fmicb.2020.01376] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
207 Moitinho-Silva L, Rodriguez E, Weidinger S. New perspectives for necrotizing soft-tissue infections pathogen detection. Br J Dermatol 2020;183:10. [PMID: 31957874 DOI: 10.1111/bjd.18796] [Reference Citation Analysis]
208 Lu Q, Xu H, Zhou L, Zhang R, Li Z, Xu P, Bai T, Wang Z, Wu G, Ren J, Jiao D, Song Y, Zhu R, Li J, Wang W, Liang R, Li L, Ma X, Zu M, Sun Y. Alterations in Faecal Metagenomics and Serum Metabolomics Indicate Management Strategies for Patients With Budd-Chiari Syndrome. Front Cell Infect Microbiol 2021;11:730091. [PMID: 34746022 DOI: 10.3389/fcimb.2021.730091] [Reference Citation Analysis]
209 Han D, Gao P, Li R, Tan P, Xie J, Zhang R, Li J. Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing. J Adv Res 2020;26:111-21. [PMID: 33133687 DOI: 10.1016/j.jare.2020.07.010] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 4.5] [Reference Citation Analysis]
210 Hopson LM, Singleton SS, David JA, Basuchoudhary A, Prast-Nielsen S, Klein P, Sen S, Mazumder R. Bioinformatics and machine learning in gastrointestinal microbiome research and clinical application. Prog Mol Biol Transl Sci 2020;176:141-78. [PMID: 33814114 DOI: 10.1016/bs.pmbts.2020.08.011] [Reference Citation Analysis]
211 Nikitin DA, Semenov MV, Chernov TI, Ksenofontova NA, Zhelezova AD, Ivanova EA, Khitrov NB, Stepanov AL. Microbiological Indicators of Soil Ecological Functions: A Review. Eurasian Soil Sc 2022;55:221-34. [DOI: 10.1134/s1064229322020090] [Reference Citation Analysis]
212 He S, Huang Z, Wang X, Fang L, Li S, Zhang Y, Zhang G. SOAPMetaS: profiling large metagenome datasets efficiently on distributed clusters. Bioinformatics 2021;37:1021-3. [PMID: 32766813 DOI: 10.1093/bioinformatics/btaa697] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
213 de Cuevillas B, Milagro FI, Tur JA, Gil-Campos M, de Miguel-Etayo P, Martínez JA, Navas-Carretero S. Fecal microbiota relationships with childhood obesity: A scoping comprehensive review. Obes Rev 2021;:e13394. [PMID: 34913242 DOI: 10.1111/obr.13394] [Reference Citation Analysis]
214 Moreno-Indias I, Lahti L, Nedyalkova M, Elbere I, Roshchupkin G, Adilovic M, Aydemir O, Bakir-Gungor B, Santa Pau EC, D'Elia D, Desai MS, Falquet L, Gundogdu A, Hron K, Klammsteiner T, Lopes MB, Marcos-Zambrano LJ, Marques C, Mason M, May P, Pašić L, Pio G, Pongor S, Promponas VJ, Przymus P, Saez-Rodriguez J, Sampri A, Shigdel R, Stres B, Suharoschi R, Truu J, Truică CO, Vilne B, Vlachakis D, Yilmaz E, Zeller G, Zomer AL, Gómez-Cabrero D, Claesson MJ. Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions. Front Microbiol 2021;12:635781. [PMID: 33692771 DOI: 10.3389/fmicb.2021.635781] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
215 Jones CB, White JR, Ernst SE, Sfanos KS, Peiffer LB. Incorporation of Data From Multiple Hypervariable Regions when Analyzing Bacterial 16S rRNA Gene Sequencing Data. Front Genet 2022;13:799615. [DOI: 10.3389/fgene.2022.799615] [Reference Citation Analysis]
216 Ungaro F, Massimino L, D'Alessio S, Danese S. The gut virome in inflammatory bowel disease pathogenesis: From metagenomics to novel therapeutic approaches. United European Gastroenterol J 2019;7:999-1007. [PMID: 31662858 DOI: 10.1177/2050640619876787] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 4.0] [Reference Citation Analysis]
217 Aguiar LM, Souza MF, de Laia ML, de Oliveira Melo J, da Costa MR, Gonçalves JF, Silva DV, Dos Santos JB. Metagenomic analysis reveals mechanisms of atrazine biodegradation promoted by tree species. Environ Pollut 2020;267:115636. [PMID: 33254605 DOI: 10.1016/j.envpol.2020.115636] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
218 Yan Y, Nguyen LH, Franzosa EA, Huttenhower C. Strain-level epidemiology of microbial communities and the human microbiome. Genome Med 2020;12:71. [PMID: 32791981 DOI: 10.1186/s13073-020-00765-y] [Cited by in Crossref: 16] [Cited by in F6Publishing: 12] [Article Influence: 8.0] [Reference Citation Analysis]
219 Bulseco AN, Vineis JH, Murphy AE, Spivak AC, Giblin AE, Tucker J, Bowen JL. Metagenomics coupled with biogeochemical rates measurements provide evidence that nitrate addition stimulates respiration in salt marsh sediments. Limnol Oceanogr 2020;65. [DOI: 10.1002/lno.11326] [Cited by in Crossref: 5] [Article Influence: 1.7] [Reference Citation Analysis]
220 Tiew PY, Mac Aogain M, Ali NABM, Thng KX, Goh K, Lau KJX, Chotirmall SH. The Mycobiome in Health and Disease: Emerging Concepts, Methodologies and Challenges. Mycopathologia 2020;185:207-31. [PMID: 31894501 DOI: 10.1007/s11046-019-00413-z] [Cited by in Crossref: 11] [Cited by in F6Publishing: 13] [Article Influence: 5.5] [Reference Citation Analysis]
221 Hu-Lieskovan S, Bhaumik S, Dhodapkar K, Grivel JJB, Gupta S, Hanks BA, Janetzki S, Kleen TO, Koguchi Y, Lund AW, Maccalli C, Mahnke YD, Novosiadly RD, Selvan SR, Sims T, Zhao Y, Maecker HT. SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery. J Immunother Cancer 2020;8:e000705. [PMID: 33268350 DOI: 10.1136/jitc-2020-000705] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
222 Ye L, Dong N, Xiong W, Li J, Li R, Heng H, Chan EWC, Chen S. High-Resolution Metagenomics of Human Gut Microbiota Generated by Nanopore and Illumina Hybrid Metagenome Assembly. Front Microbiol 2022;13:801587. [DOI: 10.3389/fmicb.2022.801587] [Reference Citation Analysis]
223 Nyholm L, Koziol A, Marcos S, Botnen AB, Aizpurua O, Gopalakrishnan S, Limborg MT, Gilbert MTP, Alberdi A. Holo-Omics: Integrated Host-Microbiota Multi-omics for Basic and Applied Biological Research. iScience 2020;23:101414. [PMID: 32777774 DOI: 10.1016/j.isci.2020.101414] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
224 Richardson M, Gottel N, Gilbert JA, Lax S. Microbial Similarity between Students in a Common Dormitory Environment Reveals the Forensic Potential of Individual Microbial Signatures. mBio 2019;10:e01054-19. [PMID: 31363029 DOI: 10.1128/mBio.01054-19] [Cited by in Crossref: 14] [Cited by in F6Publishing: 9] [Article Influence: 4.7] [Reference Citation Analysis]
225 Bui VK, Wei C. CDKAM: a taxonomic classification tool using discriminative k-mers and approximate matching strategies. BMC Bioinformatics 2020;21:468. [PMID: 33081690 DOI: 10.1186/s12859-020-03777-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
226 Ventolero MF, Wang S, Hu H, Li X. Computational analyses of bacterial strains from shotgun reads. Brief Bioinform 2022:bbac013. [PMID: 35136954 DOI: 10.1093/bib/bbac013] [Reference Citation Analysis]
227 Li G, Gao P, Zhi B, Fu B, Gao G, Chen Z, Gao M, Wu M, Ma T. The relative abundance of alkane-degrading bacteria oscillated similarly to a sinusoidal curve in an artificial ecosystem model from oil-well products: Population succession pattern in a microbial ecosystem. Environ Microbiol 2018;20:3772-83. [DOI: 10.1111/1462-2920.14382] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
228 Thomas AM, Manghi P, Asnicar F, Pasolli E, Armanini F, Zolfo M, Beghini F, Manara S, Karcher N, Pozzi C, Gandini S, Serrano D, Tarallo S, Francavilla A, Gallo G, Trompetto M, Ferrero G, Mizutani S, Shiroma H, Shiba S, Shibata T, Yachida S, Yamada T, Wirbel J, Schrotz-King P, Ulrich CM, Brenner H, Arumugam M, Bork P, Zeller G, Cordero F, Dias-Neto E, Setubal JC, Tett A, Pardini B, Rescigno M, Waldron L, Naccarati A, Segata N. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat Med 2019;25:667-78. [PMID: 30936548 DOI: 10.1038/s41591-019-0405-7] [Cited by in Crossref: 208] [Cited by in F6Publishing: 189] [Article Influence: 69.3] [Reference Citation Analysis]
229 McLaren MR, Willis AD, Callahan BJ. Consistent and correctable bias in metagenomic sequencing experiments. Elife 2019;8:e46923. [PMID: 31502536 DOI: 10.7554/eLife.46923] [Cited by in Crossref: 95] [Cited by in F6Publishing: 59] [Article Influence: 31.7] [Reference Citation Analysis]
230 Pan H, Guo R, Zhu J, Wang Q, Ju Y, Xie Y, Zheng Y, Wang Z, Li T, Liu Z, Lu L, Li F, Tong B, Xiao L, Xu X, Li R, Yuan Z, Yang H, Wang J, Kristiansen K, Jia H, Liu L. A gene catalogue of the Sprague-Dawley rat gut metagenome. Gigascience 2018;7. [PMID: 29762673 DOI: 10.1093/gigascience/giy055] [Cited by in Crossref: 35] [Cited by in F6Publishing: 31] [Article Influence: 8.8] [Reference Citation Analysis]
231 Sheppard SK, Guttman DS, Fitzgerald JR. Population genomics of bacterial host adaptation. Nat Rev Genet 2018;19:549-65. [PMID: 29973680 DOI: 10.1038/s41576-018-0032-z] [Cited by in Crossref: 98] [Cited by in F6Publishing: 74] [Article Influence: 32.7] [Reference Citation Analysis]
232 . Gut reaction. Food Sci and Tech 2021;35:21-5. [DOI: 10.1002/fsat.3501_6.x] [Reference Citation Analysis]
233 Carrizales-Sánchez AK, García-Cayuela T, Hernández-Brenes C, Senés-Guerrero C. Gut microbiota associations with metabolic syndrome and relevance of its study in pediatric subjects. Gut Microbes 2021;13:1960135. [PMID: 34491882 DOI: 10.1080/19490976.2021.1960135] [Reference Citation Analysis]
234 Mäklin T, Kallonen T, Alanko J, Samuelsen Ø, Hegstad K, Mäkinen V, Corander J, Heinz E, Honkela A. Bacterial genomic epidemiology with mixed samples. Microb Genom 2021;7. [PMID: 34779765 DOI: 10.1099/mgen.0.000691] [Reference Citation Analysis]
235 Forbes JD, Knox NC, Peterson CL, Reimer AR. Highlighting Clinical Metagenomics for Enhanced Diagnostic Decision-making: A Step Towards Wider Implementation. Comput Struct Biotechnol J 2018;16:108-20. [PMID: 30026887 DOI: 10.1016/j.csbj.2018.02.006] [Cited by in Crossref: 41] [Cited by in F6Publishing: 29] [Article Influence: 10.3] [Reference Citation Analysis]
236 da Costa Silva TA, de Paula M Jr, Silva WS, Lacorte GA. Can moderate heavy metal soil contaminations due to cement production influence the surrounding soil bacterial communities? Ecotoxicology 2021. [PMID: 34748159 DOI: 10.1007/s10646-021-02494-3] [Reference Citation Analysis]
237 Pérez-Cobas AE, Gomez-Valero L, Buchrieser C. Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses. Microb Genom 2020;6. [PMID: 32706331 DOI: 10.1099/mgen.0.000409] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 5.5] [Reference Citation Analysis]
238 Gao P. The Exposome in the Era of One Health. Environ Sci Technol 2021;55:2790-9. [DOI: 10.1021/acs.est.0c07033] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
239 Junca H, Pieper DH, Medina E. The emerging potential of microbiome transplantation on human health interventions. Computational and Structural Biotechnology Journal 2022. [DOI: 10.1016/j.csbj.2022.01.009] [Reference Citation Analysis]
240 Alneberg J, Bennke C, Beier S, Bunse C, Quince C, Ininbergs K, Riemann L, Ekman M, Jürgens K, Labrenz M, Pinhassi J, Andersson AF. Ecosystem-wide metagenomic binning enables prediction of ecological niches from genomes. Commun Biol 2020;3:119. [PMID: 32170201 DOI: 10.1038/s42003-020-0856-x] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 4.0] [Reference Citation Analysis]
241 Shaiber A, Willis AD, Delmont TO, Roux S, Chen LX, Schmid AC, Yousef M, Watson AR, Lolans K, Esen ÖC, Lee STM, Downey N, Morrison HG, Dewhirst FE, Mark Welch JL, Eren AM. Functional and genetic markers of niche partitioning among enigmatic members of the human oral microbiome. Genome Biol 2020;21:292. [PMID: 33323122 DOI: 10.1186/s13059-020-02195-w] [Cited by in Crossref: 10] [Cited by in F6Publishing: 9] [Article Influence: 5.0] [Reference Citation Analysis]
242 Conrad M, Kagan VE, Bayir H, Pagnussat GC, Head B, Traber MG, Stockwell BR. Regulation of lipid peroxidation and ferroptosis in diverse species. Genes Dev 2018;32:602-19. [PMID: 29802123 DOI: 10.1101/gad.314674.118] [Cited by in Crossref: 133] [Cited by in F6Publishing: 126] [Article Influence: 33.3] [Reference Citation Analysis]
243 Garner E, Davis BC, Milligan E, Blair MF, Keenum I, Maile-Moskowitz A, Pan J, Gnegy M, Liguori K, Gupta S, Prussin AJ 2nd, Marr LC, Heath LS, Vikesland PJ, Zhang L, Pruden A. Next generation sequencing approaches to evaluate water and wastewater quality. Water Res 2021;194:116907. [PMID: 33610927 DOI: 10.1016/j.watres.2021.116907] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
244 Kim M, Benayoun BA. The microbiome: An emerging key player in aging and longevity. Translational Medicine of Aging 2020;4:103-16. [DOI: 10.1016/j.tma.2020.07.004] [Cited by in Crossref: 12] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
245 Zolfo M, Asnicar F, Manghi P, Pasolli E, Tett A, Segata N. Profiling microbial strains in urban environments using metagenomic sequencing data. Biol Direct 2018;13:9. [PMID: 29743119 DOI: 10.1186/s13062-018-0211-z] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 4.0] [Reference Citation Analysis]
246 Wei LQ, Cheong IH, Yang GH, Li XG, Kozlakidis Z, Ding L, Liu NN, Wang H. The Application of High-Throughput Technologies for the Study of Microbiome and Cancer. Front Genet 2021;12:699793. [PMID: 34394190 DOI: 10.3389/fgene.2021.699793] [Reference Citation Analysis]
247 Yang F, Sun J, Luo H, Ren H, Zhou H, Lin Y, Han M, Chen B, Liao H, Brix S, Li J, Yang H, Kristiansen K, Zhong H. Assessment of fecal DNA extraction protocols for metagenomic studies. Gigascience 2020;9:giaa071. [PMID: 32657325 DOI: 10.1093/gigascience/giaa071] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 7.0] [Reference Citation Analysis]
248 Mannaa M, Han G, Seo YS, Park I. Evolution of Food Fermentation Processes and the Use of Multi-Omics in Deciphering the Roles of the Microbiota. Foods 2021;10:2861. [PMID: 34829140 DOI: 10.3390/foods10112861] [Reference Citation Analysis]
249 Zoledziewska M. The gut microbiota perspective for interventions in MS. Autoimmunity Reviews 2019;18:814-24. [DOI: 10.1016/j.autrev.2019.03.016] [Cited by in Crossref: 12] [Cited by in F6Publishing: 13] [Article Influence: 4.0] [Reference Citation Analysis]
250 Pienkowska K, Wiehlmann L, Tümmler B. Metagenome – Inferred bacterial replication rates in cystic fibrosis airways. Journal of Cystic Fibrosis 2019;18:653-6. [DOI: 10.1016/j.jcf.2019.01.003] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
251 Cheung SG, Goldenthal AR, Uhlemann AC, Mann JJ, Miller JM, Sublette ME. Systematic Review of Gut Microbiota and Major Depression. Front Psychiatry 2019;10:34. [PMID: 30804820 DOI: 10.3389/fpsyt.2019.00034] [Cited by in Crossref: 151] [Cited by in F6Publishing: 133] [Article Influence: 50.3] [Reference Citation Analysis]
252 Böhmer M, Ozdín D, Račko M, Lichvár M, Budiš J, Szemes T. Identification of Bacterial and Fungal Communities in the Roots of Orchids and Surrounding Soil in Heavy Metal Contaminated Area of Mining Heaps. Applied Sciences 2020;10:7367. [DOI: 10.3390/app10207367] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
253 Wang Z, Wang Y, Fuhrman JA, Sun F, Zhu S. Assessment of metagenomic assemblers based on hybrid reads of real and simulated metagenomic sequences. Brief Bioinform 2020;21:777-90. [PMID: 30860572 DOI: 10.1093/bib/bbz025] [Cited by in Crossref: 5] [Cited by in F6Publishing: 1] [Article Influence: 2.5] [Reference Citation Analysis]
254 Liu B, Thippabhotla S, Zhang J, Zhong C. DRAGoM: Classification and Quantification of Noncoding RNA in Metagenomic Data. Front Genet 2021;12:669495. [PMID: 34025724 DOI: 10.3389/fgene.2021.669495] [Reference Citation Analysis]
255 S P Galhano B, G Ferrari R, Panzenhagen P, S de Jesus AC, A Conte-Junior C. Antimicrobial Resistance Gene Detection Methods for Bacteria in Animal-Based Foods: A Brief Review of Highlights and Advantages. Microorganisms 2021;9:923. [PMID: 33925810 DOI: 10.3390/microorganisms9050923] [Reference Citation Analysis]
256 Baudry L, Foutel-Rodier T, Thierry A, Koszul R, Marbouty M. MetaTOR: A Computational Pipeline to Recover High-Quality Metagenomic Bins From Mammalian Gut Proximity-Ligation (meta3C) Libraries. Front Genet 2019;10:753. [PMID: 31481973 DOI: 10.3389/fgene.2019.00753] [Cited by in Crossref: 10] [Cited by in F6Publishing: 5] [Article Influence: 3.3] [Reference Citation Analysis]
257 Oniciuc EA, Likotrafiti E, Alvarez-Molina A, Prieto M, Santos JA, Alvarez-Ordóñez A. The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain. Genes (Basel) 2018;9:E268. [PMID: 29789467 DOI: 10.3390/genes9050268] [Cited by in Crossref: 52] [Cited by in F6Publishing: 36] [Article Influence: 13.0] [Reference Citation Analysis]
258 Wang X, Wang Z, Pan H, Qi J, Li D, Zhang L, Shen Y, Xiang Z, Li M. Captivity Influences the Gut Microbiome of Rhinopithecus roxellana. Front Microbiol 2021;12:763022. [PMID: 34950117 DOI: 10.3389/fmicb.2021.763022] [Reference Citation Analysis]
259 Yang Q, Wang Y, Wei X, Zhu J, Wang X, Xie X, Lu W. The Alterations of Vaginal Microbiome in HPV16 Infection as Identified by Shotgun Metagenomic Sequencing. Front Cell Infect Microbiol 2020;10:286. [PMID: 32656096 DOI: 10.3389/fcimb.2020.00286] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
260 Enebe MC, Babalola OO. Functional diversity of bacterial communities in the rhizosphere of maize grown on a soil under organic and inorganic fertilization. Scientific African 2022;16:e01212. [DOI: 10.1016/j.sciaf.2022.e01212] [Reference Citation Analysis]
261 Uritskiy GV, DiRuggiero J, Taylor J. MetaWRAP-a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome 2018;6:158. [PMID: 30219103 DOI: 10.1186/s40168-018-0541-1] [Cited by in Crossref: 256] [Cited by in F6Publishing: 194] [Article Influence: 64.0] [Reference Citation Analysis]
262 Borderes M, Gasc C, Prestat E, Galvão Ferrarini M, Vinga S, Boucinha L, Sagot MF. A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog. NAR Genom Bioinform 2021;3:lqab009. [PMID: 33709074 DOI: 10.1093/nargab/lqab009] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
263 Comin M, Di Camillo B, Pizzi C, Vandin F. Comparison of microbiome samples: methods and computational challenges. Brief Bioinform 2021;22:88-95. [PMID: 32577746 DOI: 10.1093/bib/bbaa121] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
264 Hu Y, Irinyi L, Hoang MTV, Eenjes T, Graetz A, Stone EA, Meyer W, Schwessinger B, Rathjen JP, Gillian Turgeon B. Inferring Species Compositions of Complex Fungal Communities from Long- and Short-Read Sequence Data. mBio. [DOI: 10.1128/mbio.02444-21] [Reference Citation Analysis]
265 Golob JL, Minot SS. In silico benchmarking of metagenomic tools for coding sequence detection reveals the limits of sensitivity and precision. BMC Bioinformatics 2020;21:459. [PMID: 33059593 DOI: 10.1186/s12859-020-03802-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
266 Lundberg DS, Pramoj Na Ayutthaya P, Strauß A, Shirsekar G, Lo WS, Lahaye T, Weigel D. Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition. Elife 2021;10:e66186. [PMID: 34292157 DOI: 10.7554/eLife.66186] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
267 Wongsurawat T, Nakagawa M, Atiq O, Coleman HN, Jenjaroenpun P, Allred JI, Trammel A, Puengrang P, Ussery DW, Nookaew I. An assessment of Oxford Nanopore sequencing for human gut metagenome profiling: A pilot study of head and neck cancer patients. J Microbiol Methods 2019;166:105739. [PMID: 31626891 DOI: 10.1016/j.mimet.2019.105739] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
268 Zeng T, Yu X, Chen Z. Applying artificial intelligence in the microbiome for gastrointestinal diseases: A review. J Gastroenterol Hepatol 2021;36:832-40. [PMID: 33880762 DOI: 10.1111/jgh.15503] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
269 Ruuskanen MO, Sommeria-Klein G, Havulinna AS, Niiranen TJ, Lahti L. Modelling spatial patterns in host-associated microbial communities. Environ Microbiol 2021;23:2374-88. [PMID: 33734553 DOI: 10.1111/1462-2920.15462] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
270 Valenzi E, Yang H, Sembrat JC, Yang L, Winters S, Nettles R, Kass DJ, Qin S, Wang X, Myerburg MM, Methé B, Fitch A, Alder JK, Benos PV, McVerry BJ, Rojas M, Morris A, Kitsios GD. Topographic heterogeneity of lung microbiota in end-stage idiopathic pulmonary fibrosis: the Microbiome in Lung Explants-2 (MiLEs-2) study. Thorax 2021;76:239-47. [PMID: 33268457 DOI: 10.1136/thoraxjnl-2020-214770] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
271 Batut B, Gravouil K, Defois C, Hiltemann S, Brugère JF, Peyretaillade E, Peyret P. ASaiM: a Galaxy-based framework to analyze microbiota data. Gigascience 2018;7. [PMID: 29790941 DOI: 10.1093/gigascience/giy057] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 4.0] [Reference Citation Analysis]
272 Marbouty M, Koszul R. Metagenomes Binning Using Proximity-Ligation Data. Methods Mol Biol 2022;2301:163-81. [PMID: 34415535 DOI: 10.1007/978-1-0716-1390-0_8] [Reference Citation Analysis]
273 Marcelino VR, Irinyi L, Eden JS, Meyer W, Holmes EC, Sorrell TC. Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities - a proof of concept under laboratory conditions. IMA Fungus 2019;10:12. [PMID: 32355612 DOI: 10.1186/s43008-019-0012-8] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 2.7] [Reference Citation Analysis]
274 Marvasi M, Cavalieri D, Mastromei G, Casaccia A, Perito B. Omics technologies for an in-depth investigation of biodeterioration of cultural heritage. International Biodeterioration & Biodegradation 2019;144:104736. [DOI: 10.1016/j.ibiod.2019.104736] [Cited by in Crossref: 20] [Cited by in F6Publishing: 5] [Article Influence: 6.7] [Reference Citation Analysis]
275 Li H, Li H. Introduction to Special Issue on Statistics in Microbiome and Metagenomics. Stat Biosci 2021;13:197-9. [DOI: 10.1007/s12561-021-09307-5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
276 Pabbathi NPP, Velidandi A, Tavarna T, Gupta S, Raj RS, Gandam PK, Baadhe RR. Role of metagenomics in prospecting novel endoglucanases, accentuating functional metagenomics approach in second-generation biofuel production: a review. Biomass Convers Biorefin 2021;:1-28. [PMID: 33437563 DOI: 10.1007/s13399-020-01186-y] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 4.0] [Reference Citation Analysis]
277 Alberdi A, Andersen SB, Limborg MT, Dunn RR, Gilbert MTP. Disentangling host-microbiota complexity through hologenomics. Nat Rev Genet 2021. [PMID: 34675394 DOI: 10.1038/s41576-021-00421-0] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
278 Snelson M, Biruete A, McFarlane C, Campbell K. A Renal Clinician's Guide to the Gut Microbiota. J Ren Nutr 2020;30:384-95. [PMID: 31928802 DOI: 10.1053/j.jrn.2019.11.002] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
279 Galloway-Peña J, Hanson B. Tools for Analysis of the Microbiome. Dig Dis Sci 2020;65:674-85. [PMID: 32002757 DOI: 10.1007/s10620-020-06091-y] [Cited by in Crossref: 12] [Cited by in F6Publishing: 13] [Article Influence: 6.0] [Reference Citation Analysis]
280 Han P, Gu JQ, Li LS, Wang XY, Wang HT, Wang Y, Chang C, Sun JL. The Association Between Intestinal Bacteria and Allergic Diseases-Cause or Consequence? Front Cell Infect Microbiol 2021;11:650893. [PMID: 33937097 DOI: 10.3389/fcimb.2021.650893] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
281 Qiao L, Liu X, Zhang S, Zhang L, Li X, Hu X, Zhao Q, Wang Q, Yu C. Distribution of the microbial community and antibiotic resistance genes in farmland surrounding gold tailings: A metagenomics approach. Sci Total Environ 2021;779:146502. [PMID: 34030239 DOI: 10.1016/j.scitotenv.2021.146502] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
282 [DOI: 10.1101/620666] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
283 Habibzadeh P, Mofatteh M, Silawi M, Ghavami S, Faghihi MA. Molecular diagnostic assays for COVID-19: an overview. Crit Rev Clin Lab Sci 2021;58:385-98. [PMID: 33595397 DOI: 10.1080/10408363.2021.1884640] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
284 Delanka-pedige HM, Cheng X, Munasinghe-arachchige SP, Abeysiriwardana-arachchige IS, Xu J, Nirmalakhandan N, Zhang Y. Metagenomic insights into virus removal performance of an algal-based wastewater treatment system utilizing Galdieria sulphuraria. Algal Research 2020;47:101865. [DOI: 10.1016/j.algal.2020.101865] [Cited by in Crossref: 18] [Cited by in F6Publishing: 8] [Article Influence: 9.0] [Reference Citation Analysis]
285 Almeida A, Shao Y. Genome watch: Keeping tally in the microbiome. Nat Rev Microbiol 2018;16:124. [PMID: 29379216 DOI: 10.1038/nrmicro.2018.13] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
286 Bahram M, Netherway T, Frioux C, Ferretti P, Coelho LP, Geisen S, Bork P, Hildebrand F. Metagenomic assessment of the global diversity and distribution of bacteria and fungi. Environ Microbiol 2021;23:316-26. [PMID: 33185929 DOI: 10.1111/1462-2920.15314] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
287 Münch PC, Franzosa EA, Stecher B, McHardy AC, Huttenhower C. Identification of Natural CRISPR Systems and Targets in the Human Microbiome. Cell Host Microbe 2021;29:94-106.e4. [PMID: 33217332 DOI: 10.1016/j.chom.2020.10.010] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
288 Bedoya K, Coltell O, Cabarcas F, Alzate JF. Metagenomic assessment of the microbial community and methanogenic pathways in biosolids from a municipal wastewater treatment plant in Medellín, Colombia. Sci Total Environ 2019;648:572-81. [PMID: 30121535 DOI: 10.1016/j.scitotenv.2018.08.119] [Cited by in Crossref: 14] [Cited by in F6Publishing: 9] [Article Influence: 3.5] [Reference Citation Analysis]
289 Kabwe M, Dashper S, Bachrach G, Tucci J. Bacteriophage manipulation of the microbiome associated with tumour microenvironments-can this improve cancer therapeutic response? FEMS Microbiol Rev 2021:fuab017. [PMID: 33765142 DOI: 10.1093/femsre/fuab017] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
290 Doña J, Virrueta Herrera S, Nyman T, Kunnasranta M, Johnson KP. Patterns of Microbiome Variation Among Infrapopulations of Permanent Bloodsucking Parasites. Front Microbiol 2021;12:642543. [PMID: 33935998 DOI: 10.3389/fmicb.2021.642543] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
291 Manara S, Asnicar F, Beghini F, Bazzani D, Cumbo F, Zolfo M, Nigro E, Karcher N, Manghi P, Metzger MI, Pasolli E, Segata N. Microbial genomes from non-human primate gut metagenomes expand the primate-associated bacterial tree of life with over 1000 novel species. Genome Biol 2019;20:299. [PMID: 31883524 DOI: 10.1186/s13059-019-1923-9] [Cited by in Crossref: 19] [Cited by in F6Publishing: 14] [Article Influence: 6.3] [Reference Citation Analysis]
292 Ransom EM, Potter RF, Dantas G, Burnham CD. Genomic Prediction of Antimicrobial Resistance: Ready or Not, Here It Comes! Clin Chem 2020;66:1278-89. [PMID: 32918462 DOI: 10.1093/clinchem/hvaa172] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
293 Brunel C, Pouteau R, Dawson W, Pester M, Ramirez KS, van Kleunen M. Towards Unraveling Macroecological Patterns in Rhizosphere Microbiomes. Trends in Plant Science 2020;25:1017-29. [DOI: 10.1016/j.tplants.2020.04.015] [Cited by in Crossref: 9] [Cited by in F6Publishing: 4] [Article Influence: 4.5] [Reference Citation Analysis]
294 Saary P, Mitchell AL, Finn RD. Estimating the quality of eukaryotic genomes recovered from metagenomic analysis with EukCC. Genome Biol 2020;21:244. [PMID: 32912302 DOI: 10.1186/s13059-020-02155-4] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
295 [DOI: 10.1101/2020.05.19.103937] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
296 Shade A, Dunn RR, Blowes SA, Keil P, Bohannan BJ, Herrmann M, Küsel K, Lennon JT, Sanders NJ, Storch D, Chase J. Macroecology to Unite All Life, Large and Small. Trends in Ecology & Evolution 2018;33:731-44. [DOI: 10.1016/j.tree.2018.08.005] [Cited by in Crossref: 62] [Cited by in F6Publishing: 33] [Article Influence: 15.5] [Reference Citation Analysis]
297 Harkins P, Burke E, Swales C, Silman A. 'All disease begins in the gut'-the role of the intestinal microbiome in ankylosing spondylitis. Rheumatol Adv Pract 2021;5:rkab063. [PMID: 34557624 DOI: 10.1093/rap/rkab063] [Reference Citation Analysis]
298 Almeida A, Mitchell AL, Boland M, Forster SC, Gloor GB, Tarkowska A, Lawley TD, Finn RD. A new genomic blueprint of the human gut microbiota. Nature 2019;568:499-504. [PMID: 30745586 DOI: 10.1038/s41586-019-0965-1] [Cited by in Crossref: 334] [Cited by in F6Publishing: 306] [Article Influence: 111.3] [Reference Citation Analysis]
299 Zhou J, Yu X, Liu J, Qin W, He Z, Stahl D, Jiao N, Zhou J, Tu Q. VB12Path for Accurate Metagenomic Profiling of Microbially Driven Cobalamin Synthesis Pathways. mSystems 2021;6:e0049721. [PMID: 34060913 DOI: 10.1128/mSystems.00497-21] [Reference Citation Analysis]
300 Yang Q, Cahn JKB, Piel J, Song Y, Zhang W, Lin H, Kormas KA. Marine Sponge Endosymbionts: Structural and Functional Specificity of the Microbiome within Euryspongia arenaria Cells. Microbiol Spectr. [DOI: 10.1128/spectrum.02296-21] [Reference Citation Analysis]
301 Rahman MA, Rangwala H. IDMIL: an alignment-free Interpretable Deep Multiple Instance Learning (MIL) for predicting disease from whole-metagenomic data. Bioinformatics 2020;36:i39-47. [PMID: 32657370 DOI: 10.1093/bioinformatics/btaa477] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
302 Meyer F, Lesker TR, Koslicki D, Fritz A, Gurevich A, Darling AE, Sczyrba A, Bremges A, McHardy AC. Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit. Nat Protoc 2021;16:1785-801. [PMID: 33649565 DOI: 10.1038/s41596-020-00480-3] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
303 Peters K, Treutler H, Döll S, Kindt ASD, Hankemeier T, Neumann S. Chemical Diversity and Classification of Secondary Metabolites in Nine Bryophyte Species. Metabolites 2019;9:E222. [PMID: 31614655 DOI: 10.3390/metabo9100222] [Cited by in Crossref: 11] [Cited by in F6Publishing: 4] [Article Influence: 3.7] [Reference Citation Analysis]
304 Nguyen TT, Hathaway H, Kosciolek T, Knight R, Jeste DV. Gut microbiome in serious mental illnesses: A systematic review and critical evaluation. Schizophr Res 2021;234:24-40. [PMID: 31495702 DOI: 10.1016/j.schres.2019.08.026] [Cited by in Crossref: 16] [Cited by in F6Publishing: 13] [Article Influence: 5.3] [Reference Citation Analysis]
305 Kroeger ME, Meredith LK, Meyer KM, Webster KD, de Camargo PB, de Souza LF, Tsai SM, van Haren J, Saleska S, Bohannan BJM, Rodrigues JLM, Berenguer E, Barlow J, Nüsslein K. Rainforest-to-pasture conversion stimulates soil methanogenesis across the Brazilian Amazon. ISME J 2021;15:658-72. [PMID: 33082572 DOI: 10.1038/s41396-020-00804-x] [Cited by in Crossref: 4] [Article Influence: 2.0] [Reference Citation Analysis]
306 Dilthey AT, Jain C, Koren S, Phillippy AM. Strain-level metagenomic assignment and compositional estimation for long reads with MetaMaps. Nat Commun 2019;10:3066. [PMID: 31296857 DOI: 10.1038/s41467-019-10934-2] [Cited by in Crossref: 33] [Cited by in F6Publishing: 26] [Article Influence: 11.0] [Reference Citation Analysis]
307 Saleem F, Azim MK, Mustafa A, Kori JA, Hussain MS. Metagenomic profiling of fresh water lakes at different altitudes in Pakistan. Ecological Informatics 2019;51:73-81. [DOI: 10.1016/j.ecoinf.2019.02.013] [Cited by in Crossref: 4] [Article Influence: 1.3] [Reference Citation Analysis]
308 Chandran H, Meena M, Sharma K. Microbial Biodiversity and Bioremediation Assessment Through Omics Approaches. Front Environ Chem 2020;1:570326. [DOI: 10.3389/fenvc.2020.570326] [Cited by in Crossref: 25] [Cited by in F6Publishing: 6] [Article Influence: 12.5] [Reference Citation Analysis]
309 Hooper R, Brealey JC, van der Valk T, Alberdi A, Durban JW, Fearnbach H, Robertson KM, Baird RW, Bradley Hanson M, Wade P, Gilbert MTP, Morin PA, Wolf JBW, Foote AD, Guschanski K. Host-derived population genomics data provides insights into bacterial and diatom composition of the killer whale skin. Mol Ecol 2019;28:484-502. [PMID: 30187987 DOI: 10.1111/mec.14860] [Cited by in Crossref: 25] [Cited by in F6Publishing: 23] [Article Influence: 6.3] [Reference Citation Analysis]
310 Quistad SD, Doulcier G, Rainey PB. Experimental manipulation of selfish genetic elements links genes to microbial community function. Philos Trans R Soc Lond B Biol Sci 2020;375:20190681. [PMID: 32200751 DOI: 10.1098/rstb.2019.0681] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
311 Westaway JAF, Huerlimann R, Miller CM, Kandasamy Y, Norton R, Rudd D. Methods for exploring the faecal microbiome of premature infants: a review. Matern Health Neonatol Perinatol 2021;7:11. [PMID: 33685524 DOI: 10.1186/s40748-021-00131-9] [Reference Citation Analysis]
312 Cantalupo PG, Pipas JM. Detecting viral sequences in NGS data. Current Opinion in Virology 2019;39:41-8. [DOI: 10.1016/j.coviro.2019.07.010] [Cited by in Crossref: 17] [Cited by in F6Publishing: 14] [Article Influence: 5.7] [Reference Citation Analysis]
313 Jean-Pierre F, Henson MA, O'Toole GA. Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists. Front Mol Biosci 2021;8:634479. [PMID: 33681294 DOI: 10.3389/fmolb.2021.634479] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
314 Sridhar K, Singh A, Butzmann A, Jangam D, Ohgami RS. Molecular genetic testing methodologies in hematopoietic diseases: current and future methods. Int J Lab Hematol 2019;41 Suppl 1:102-16. [PMID: 31069972 DOI: 10.1111/ijlh.13024] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
315 Kui L, Chen B, Chen J, Sharifi R, Dong Y, Zhang Z, Miao J. A Comparative Analysis on the Structure and Function of the Panax notoginseng Rhizosphere Microbiome. Front Microbiol 2021;12:673512. [PMID: 34177857 DOI: 10.3389/fmicb.2021.673512] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
316 Teh JJ, Berendsen EM, Hoedt EC, Kang S, Zhang J, Zhang F, Liu Q, Hamilton AL, Wilson-O'Brien A, Ching J, Sung JJY, Yu J, Ng SC, Kamm MA, Morrison M. Novel strain-level resolution of Crohn's disease mucosa-associated microbiota via an ex vivo combination of microbe culture and metagenomic sequencing. ISME J 2021. [PMID: 34035441 DOI: 10.1038/s41396-021-00991-1] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
317 Sun H, Guan LL. Feedomics: Promises for food security with sustainable food animal production. TrAC Trends in Analytical Chemistry 2018;107:130-41. [DOI: 10.1016/j.trac.2018.07.025] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
318 Li C, Chng KR, Kwah JS, Av-Shalom TV, Tucker-Kellogg L, Nagarajan N. An expectation-maximization algorithm enables accurate ecological modeling using longitudinal microbiome sequencing data. Microbiome 2019;7:118. [PMID: 31439018 DOI: 10.1186/s40168-019-0729-z] [Cited by in Crossref: 16] [Cited by in F6Publishing: 11] [Article Influence: 5.3] [Reference Citation Analysis]
319 Schuurman AR, Reijnders TDY, Kullberg RFJ, Butler JM, van der Poll T, Wiersinga WJ. Sepsis: deriving biological meaning and clinical applications from high-dimensional data. Intensive Care Med Exp 2021;9:27. [PMID: 33961170 DOI: 10.1186/s40635-021-00383-x] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
320 Romanis CS, Pearson LA, Neilan BA. Cyanobacterial blooms in wastewater treatment facilities: Significance and emerging monitoring strategies. J Microbiol Methods 2021;180:106123. [PMID: 33316292 DOI: 10.1016/j.mimet.2020.106123] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
321 Sun Z, Huang S, Zhu P, Tzehau L, Zhao H, Lv J, Zhang R, Zhou L, Niu Q, Wang X, Zhang M, Jing G, Bao Z, Liu J, Wang S, Xu J. Species-resolved sequencing of low-biomass or degraded microbiomes using 2bRAD-M. Genome Biol 2022;23. [DOI: 10.1186/s13059-021-02576-9] [Reference Citation Analysis]
322 Malaterre C, Dussault AC, Mermans E, Barker G, Beisner BE, Bouchard F, Desjardins E, Handa IT, Kembel SW, Lajoie G, Maris V, Munson AD, Odenbaugh J, Poisot T, Shapiro BJ, Suttle CA. Functional Diversity: An Epistemic Roadmap. BioScience 2019;69:800-11. [DOI: 10.1093/biosci/biz089] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
323 Liang Q, Bible PW, Liu Y, Zou B, Wei L. DeepMicrobes: taxonomic classification for metagenomics with deep learning. NAR Genom Bioinform 2020;2:lqaa009. [PMID: 33575556 DOI: 10.1093/nargab/lqaa009] [Cited by in Crossref: 22] [Cited by in F6Publishing: 8] [Article Influence: 11.0] [Reference Citation Analysis]
324 Tanaka M, Onizuka S, Mishima R, Nakayama J. Cultural isolation of spore-forming bacteria in human feces using bile acids. Sci Rep 2020;10:15041. [PMID: 32929101 DOI: 10.1038/s41598-020-71883-1] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
325 De Filippis F, Pasolli E, Ercolini D. The food-gut axis: lactic acid bacteria and their link to food, the gut microbiome and human health. FEMS Microbiol Rev 2020;44:454-89. [PMID: 32556166 DOI: 10.1093/femsre/fuaa015] [Cited by in Crossref: 16] [Cited by in F6Publishing: 15] [Article Influence: 16.0] [Reference Citation Analysis]
326 Guzzo GL, Andrews JM, Weyrich LS. The Neglected Gut Microbiome: Fungi, Protozoa, and Bacteriophages in Inflammatory Bowel Disease. Inflammatory Bowel Diseases 2022. [DOI: 10.1093/ibd/izab343] [Reference Citation Analysis]
327 Royalty TM, Steen AD. Theoretical and Simulation-Based Investigation of the Relationship between Sequencing Effort, Microbial Community Richness, and Diversity in Binning Metagenome-Assembled Genomes. mSystems 2019;4:e00384-19. [PMID: 31530648 DOI: 10.1128/mSystems.00384-19] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
328 Alessandri G, Milani C, Mancabelli L, Mangifesta M, Lugli GA, Viappiani A, Duranti S, Turroni F, Ossiprandi MC, van Sinderen D, Ventura M. Metagenomic dissection of the canine gut microbiota: insights into taxonomic, metabolic and nutritional features. Environ Microbiol 2019;21:1331-43. [PMID: 30680877 DOI: 10.1111/1462-2920.14540] [Cited by in Crossref: 32] [Cited by in F6Publishing: 27] [Article Influence: 10.7] [Reference Citation Analysis]
329 Graf EH, Pancholi P. Appropriate Use and Future Directions of Molecular Diagnostic Testing. Curr Infect Dis Rep 2020;22:5. [PMID: 32030534 DOI: 10.1007/s11908-020-0714-5] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 2.5] [Reference Citation Analysis]
330 Parducci L, Alsos IG, Unneberg P, Pedersen MW, Han L, Lammers Y, Salonen JS, Väliranta MM, Slotte T, Wohlfarth B. Shotgun Environmental DNA, Pollen, and Macrofossil Analysis of Lateglacial Lake Sediments From Southern Sweden. Front Ecol Evol 2019;7:189. [DOI: 10.3389/fevo.2019.00189] [Cited by in Crossref: 24] [Cited by in F6Publishing: 2] [Article Influence: 8.0] [Reference Citation Analysis]
331 Ghanbari Maman L, Palizban F, Fallah Atanaki F, Elmi Ghiasi N, Ariaeenejad S, Ghaffari MR, Hosseini Salekdeh G, Kavousi K. Co-abundance analysis reveals hidden players associated with high methane yield phenotype in sheep rumen microbiome. Sci Rep 2020;10:4995. [PMID: 32193482 DOI: 10.1038/s41598-020-61942-y] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
332 Harrison XA, Cameron SJS. Analytical approaches for microbiome research. In: Antwis RE, Harrison XA, Cox MJ, editors. Microbiomes of Soils, Plants and Animals. Cambridge University Press; 2020. pp. 8-28. [DOI: 10.1017/9781108654418.002] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
333 Xie H, Zhao Q, Shi M, Kong W, Mu W, Li B, Zhao J, Zhao C, Jia J, Liu J, Shi L. Biological Ingredient Analysis of Traditional Herbal Patent Medicine Fuke Desheng Wan Using the Shotgun Metabarcoding Approach. Front Pharmacol 2021;12:607197. [PMID: 34483893 DOI: 10.3389/fphar.2021.607197] [Reference Citation Analysis]
334 Grenni P. Antimicrobial Resistance in Rivers: A Review of the Genes Detected and New Challenges. Environ Toxicol Chem 2022;41:687-714. [PMID: 35191071 DOI: 10.1002/etc.5289] [Reference Citation Analysis]
335 Arumugam K, Bağcı C, Bessarab I, Beier S, Buchfink B, Górska A, Qiu G, Huson DH, Williams RBH. Annotated bacterial chromosomes from frame-shift-corrected long-read metagenomic data. Microbiome 2019;7:61. [PMID: 30992083 DOI: 10.1186/s40168-019-0665-y] [Cited by in Crossref: 32] [Cited by in F6Publishing: 22] [Article Influence: 10.7] [Reference Citation Analysis]
336 Leipold L, Dobrijevic D, Jeffries JWE, Bawn M, Moody TS, Ward JM, Hailes HC. The identification and use of robust transaminases from a domestic drain metagenome. Green Chem 2019;21:75-86. [PMID: 30930686 DOI: 10.1039/c8gc02986e] [Cited by in Crossref: 27] [Cited by in F6Publishing: 8] [Article Influence: 6.8] [Reference Citation Analysis]
337 Siekaniec G, Roux E, Lemane T, Guédon E, Nicolas J. Identification of isolated or mixed strains from long reads: a challenge met on Streptococcus thermophilus using a MinION sequencer. Microb Genom 2021;7. [PMID: 34812718 DOI: 10.1099/mgen.0.000654] [Reference Citation Analysis]
338 Seol D, Jhang SY, Kim H, Kim SY, Kwak HS, Kim SH, Lee W, Park S, Kim H, Cho S, Kwak W. Accurate and Strict Identification of Probiotic Species Based on Coverage of Whole-Metagenome Shotgun Sequencing Data. Front Microbiol 2019;10:1683. [PMID: 31440213 DOI: 10.3389/fmicb.2019.01683] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
339 Boutin S, Dalpke AH. The Microbiome: A Reservoir to Discover New Antimicrobials Agents. CTMC 2020;20:1291-9. [DOI: 10.2174/1568026620666200320112731] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
340 Zhang B, Xu S, Xu W, Chen Q, Chen Z, Yan C, Fan Y, Zhang H, Liu Q, Yang J, Yang J, Xiao C, Xu H, Ren J. Leveraging Fecal Bacterial Survey Data to Predict Colorectal Tumors. Front Genet 2019;10:447. [PMID: 31191599 DOI: 10.3389/fgene.2019.00447] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 1.7] [Reference Citation Analysis]
341 Branda JA, Steere AC. Laboratory Diagnosis of Lyme Borreliosis. Clin Microbiol Rev 2021;34:e00018-19. [PMID: 33504503 DOI: 10.1128/CMR.00018-19] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
342 Tanentzap AJ, Fitch A, Orland C, Emilson EJS, Yakimovich KM, Osterholz H, Dittmar T. Chemical and microbial diversity covary in fresh water to influence ecosystem functioning. Proc Natl Acad Sci U S A 2019;116:24689-95. [PMID: 31740592 DOI: 10.1073/pnas.1904896116] [Cited by in Crossref: 24] [Cited by in F6Publishing: 18] [Article Influence: 8.0] [Reference Citation Analysis]
343 Hardwick SA, Chen WY, Wong T, Kanakamedala BS, Deveson IW, Ongley SE, Santini NS, Marcellin E, Smith MA, Nielsen LK, Lovelock CE, Neilan BA, Mercer TR. Synthetic microbe communities provide internal reference standards for metagenome sequencing and analysis. Nat Commun 2018;9:3096. [PMID: 30082706 DOI: 10.1038/s41467-018-05555-0] [Cited by in Crossref: 40] [Cited by in F6Publishing: 32] [Article Influence: 10.0] [Reference Citation Analysis]
344 Borroni D, Romano V, Kaye SB, Somerville T, Napoli L, Fasolo A, Gallon P, Ponzin D, Esposito A, Ferrari S. Metagenomics in ophthalmology: current findings and future prospectives. BMJ Open Ophthalmol 2019;4:e000248. [PMID: 31276030 DOI: 10.1136/bmjophth-2018-000248] [Cited by in Crossref: 15] [Cited by in F6Publishing: 13] [Article Influence: 5.0] [Reference Citation Analysis]
345 Legrand TP, Wynne JW, Weyrich LS, Oxley AP. A microbial sea of possibilities: current knowledge and prospects for an improved understanding of the fish microbiome. Rev Aquacult 2020;12:1101-34. [DOI: 10.1111/raq.12375] [Cited by in Crossref: 33] [Cited by in F6Publishing: 8] [Article Influence: 11.0] [Reference Citation Analysis]
346 Norvaisas P, Cabreiro F. Pharmacology in the age of the holobiont. Current Opinion in Systems Biology 2018;10:34-42. [DOI: 10.1016/j.coisb.2018.05.006] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
347 Reiter T, Brooks PT, Irber L, Joslin SEK, Reid CM, Scott C, Brown CT, Pierce-Ward NT. Streamlining data-intensive biology with workflow systems. Gigascience 2021;10:giaa140. [PMID: 33438730 DOI: 10.1093/gigascience/giaa140] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
348 Maguire F, Jia B, Gray KL, Lau WYV, Beiko RG, Brinkman FSL. Metagenome-assembled genome binning methods with short reads disproportionately fail for plasmids and genomic Islands. Microb Genom 2020;6. [PMID: 33001022 DOI: 10.1099/mgen.0.000436] [Cited by in Crossref: 13] [Cited by in F6Publishing: 10] [Article Influence: 13.0] [Reference Citation Analysis]
349 Taylor SL, O'Farrell HE, Simpson JL, Yang IA, Rogers GB. The contribution of respiratory microbiome analysis to a treatable traits model of care. Respirology 2019;24:19-28. [PMID: 30282116 DOI: 10.1111/resp.13411] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 1.8] [Reference Citation Analysis]
350 Bacci G, Taccetti G, Dolce D, Armanini F, Segata N, Di Cesare F, Lucidi V, Fiscarelli E, Morelli P, Casciaro R, Negroni A, Mengoni A, Bevivino A. Untargeted Metagenomic Investigation of the Airway Microbiome of Cystic Fibrosis Patients with Moderate-Severe Lung Disease. Microorganisms 2020;8:E1003. [PMID: 32635564 DOI: 10.3390/microorganisms8071003] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 4.5] [Reference Citation Analysis]
351 Bharucha T, Oeser C, Balloux F, Brown JR, Carbo EC, Charlett A, Chiu CY, Claas ECJ, de Goffau MC, de Vries JJC, Eloit M, Hopkins S, Huggett JF, MacCannell D, Morfopoulou S, Nath A, O'Sullivan DM, Reoma LB, Shaw LP, Sidorov I, Simner PJ, Van Tan L, Thomson EC, van Dorp L, Wilson MR, Breuer J, Field N. STROBE-metagenomics: a STROBE extension statement to guide the reporting of metagenomics studies. Lancet Infect Dis 2020;20:e251-60. [PMID: 32768390 DOI: 10.1016/S1473-3099(20)30199-7] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 4.5] [Reference Citation Analysis]
352 Mills RH, Vázquez-Baeza Y, Zhu Q, Jiang L, Gaffney J, Humphrey G, Smarr L, Knight R, Gonzalez DJ. Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease. mSystems 2019;4:e00337-18. [PMID: 30801026 DOI: 10.1128/mSystems.00337-18] [Cited by in Crossref: 19] [Cited by in F6Publishing: 12] [Article Influence: 6.3] [Reference Citation Analysis]
353 Alberdi A, Gilbert MTP. A guide to the application of Hill numbers to DNA‐based diversity analyses. Mol Ecol Resour 2019;19:804-17. [DOI: 10.1111/1755-0998.13014] [Cited by in Crossref: 33] [Cited by in F6Publishing: 18] [Article Influence: 11.0] [Reference Citation Analysis]
354 Zolfo M, Pinto F, Asnicar F, Manghi P, Tett A, Bushman FD, Segata N. Detecting contamination in viromes using ViromeQC. Nat Biotechnol 2019;37:1408-12. [PMID: 31748692 DOI: 10.1038/s41587-019-0334-5] [Cited by in Crossref: 28] [Cited by in F6Publishing: 21] [Article Influence: 14.0] [Reference Citation Analysis]
355 Overmann J, Huang S, Nübel U, Hahnke RL, Tindall BJ. Relevance of phenotypic information for the taxonomy of not-yet-cultured microorganisms. Syst Appl Microbiol 2019;42:22-9. [PMID: 30197212 DOI: 10.1016/j.syapm.2018.08.009] [Cited by in Crossref: 15] [Cited by in F6Publishing: 11] [Article Influence: 3.8] [Reference Citation Analysis]
356 Goh KM, Shahar S, Chan KG, Chong CS, Amran SI, Sani MH, Zakaria II, Kahar UM. Current Status and Potential Applications of Underexplored Prokaryotes. Microorganisms 2019;7:E468. [PMID: 31635256 DOI: 10.3390/microorganisms7100468] [Cited by in Crossref: 8] [Cited by in F6Publishing: 3] [Article Influence: 2.7] [Reference Citation Analysis]
357 Thomas AM, Segata N. Multiple levels of the unknown in microbiome research. BMC Biol 2019;17:48. [PMID: 31189463 DOI: 10.1186/s12915-019-0667-z] [Cited by in Crossref: 35] [Cited by in F6Publishing: 24] [Article Influence: 11.7] [Reference Citation Analysis]
358 Fang X, Vázquez-Baeza Y, Elijah E, Vargas F, Ackermann G, Humphrey G, Lau R, Weldon KC, Sanders JG, Panitchpakdi M, Carpenter C, Jarmusch AK, Neill J, Miralles A, Dulai P, Singh S, Tsai M, Swafford AD, Smarr L, Boyle DL, Palsson BO, Chang JT, Dorrestein PC, Sandborn WJ, Knight R, Boland BS. Gastrointestinal Surgery for Inflammatory Bowel Disease Persistently Lowers Microbiome and Metabolome Diversity. Inflamm Bowel Dis 2021;27:603-16. [PMID: 33026068 DOI: 10.1093/ibd/izaa262] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
359 Mancin L, Rollo I, Mota JF, Piccini F, Carletti M, Susto GA, Valle G, Paoli A. Optimizing Microbiota Profiles for Athletes. Exerc Sport Sci Rev. 2021;49:42-49. [PMID: 33044333 DOI: 10.1249/jes.0000000000000236] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
360 Utembe W, Kamng'ona AW. Gut microbiota-mediated pesticide toxicity in humans: Methodological issues and challenges in the risk assessment of pesticides. Chemosphere 2021;271:129817. [PMID: 33736210 DOI: 10.1016/j.chemosphere.2021.129817] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
361 Li LG, Huang Q, Yin X, Zhang T. Source tracking of antibiotic resistance genes in the environment - Challenges, progress, and prospects. Water Res 2020;185:116127. [PMID: 33086465 DOI: 10.1016/j.watres.2020.116127] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 5.5] [Reference Citation Analysis]
362 McInnes RS, McCallum GE, Lamberte LE, van Schaik W. Horizontal transfer of antibiotic resistance genes in the human gut microbiome. Curr Opin Microbiol 2020;53:35-43. [PMID: 32143027 DOI: 10.1016/j.mib.2020.02.002] [Cited by in Crossref: 37] [Cited by in F6Publishing: 29] [Article Influence: 18.5] [Reference Citation Analysis]
363 Hong X, Qin P, Huang K, Ding X, Ma J, Xuan Y, Zhu X, Peng D, Wang B. Association between polycystic ovary syndrome and the vaginal microbiome: A case-control study. Clin Endocrinol (Oxf) 2020;93:52-60. [PMID: 32311120 DOI: 10.1111/cen.14198] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 5.0] [Reference Citation Analysis]
364 Zhang Y, Zhang C, Li B, Li Y, He XZ, Li A, Wu W, Duan SX, Qiu FZ, Wang J, Shen XX, Yang MJ, Li X, Ma XJ. VSITA, an Improved Approach of Target Amplification in the Identification of Viral Pathogens. Biomed Environ Sci 2018;31:272-9. [PMID: 29773090 DOI: 10.3967/bes2018.035] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
365 Deng Z, Zhang J, Li J, Zhang X. Application of Deep Learning in Plant-Microbiota Association Analysis. Front Genet 2021;12:697090. [PMID: 34691142 DOI: 10.3389/fgene.2021.697090] [Reference Citation Analysis]
366 Azevedo‐silva D, Rasmussen J, Carneiro M, Gilbert M, Azevedo H. Feasibility of applying shotgun metagenomic analyses to grapevine leaf, rhizosphere and soil microbiome characterisation. Australian Journal of Grape and Wine Research 2021;27:519-26. [DOI: 10.1111/ajgw.12508] [Reference Citation Analysis]
367 Almeida A, Mitchell AL, Tarkowska A, Finn RD. Benchmarking taxonomic assignments based on 16S rRNA gene profiling of the microbiota from commonly sampled environments. Gigascience 2018;7. [PMID: 29762668 DOI: 10.1093/gigascience/giy054] [Cited by in Crossref: 53] [Cited by in F6Publishing: 38] [Article Influence: 13.3] [Reference Citation Analysis]
368 Cuna A, Morowitz MJ, Ahmed I, Umar S, Sampath V. Dynamics of the preterm gut microbiome in health and disease. Am J Physiol Gastrointest Liver Physiol 2021;320:G411-9. [PMID: 33439103 DOI: 10.1152/ajpgi.00399.2020] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
369 Cammarota G, Ianiro G, Ahern A, Carbone C, Temko A, Claesson MJ, Gasbarrini A, Tortora G. Gut microbiome, big data and machine learning to promote precision medicine for cancer. Nat Rev Gastroenterol Hepatol 2020;17:635-48. [DOI: 10.1038/s41575-020-0327-3] [Cited by in Crossref: 31] [Cited by in F6Publishing: 25] [Article Influence: 15.5] [Reference Citation Analysis]
370 Schön ME, Eme L, Ettema TJG. PhyloMagnet: fast and accurate screening of short-read meta-omics data using gene-centric phylogenetics. Bioinformatics 2020;36:1718-24. [PMID: 31647547 DOI: 10.1093/bioinformatics/btz799] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
371 McLoughlin S, Spillane C, Claffey N, Smith PE, O'Rourke T, Diskin MG, Waters SM. Rumen Microbiome Composition Is Altered in Sheep Divergent in Feed Efficiency. Front Microbiol 2020;11:1981. [PMID: 32983009 DOI: 10.3389/fmicb.2020.01981] [Cited by in Crossref: 7] [Cited by in F6Publishing: 10] [Article Influence: 3.5] [Reference Citation Analysis]
372 Beghini F, McIver LJ, Blanco-Míguez A, Dubois L, Asnicar F, Maharjan S, Mailyan A, Manghi P, Scholz M, Thomas AM, Valles-Colomer M, Weingart G, Zhang Y, Zolfo M, Huttenhower C, Franzosa EA, Segata N. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife 2021;10:e65088. [PMID: 33944776 DOI: 10.7554/eLife.65088] [Cited by in Crossref: 17] [Cited by in F6Publishing: 18] [Article Influence: 17.0] [Reference Citation Analysis]
373 Manenzhe RI, Dube FS, Wright M, Lennard K, Mounaud S, Lo SW, Zar HJ, Nierman WC, Nicol MP, Moodley C. Characterization of Pneumococcal Colonization Dynamics and Antimicrobial Resistance Using Shotgun Metagenomic Sequencing in Intensively Sampled South African Infants. Front Public Health 2020;8:543898. [PMID: 33072693 DOI: 10.3389/fpubh.2020.543898] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
374 Deschamps O, Ortonne N, Hüe S, Rodriguez C, Deschodt C, Hirsch G, Colin A, Grégoire L, Delfau-Larue MH, Chosidow O, Wolkenstein P, Ingen-Housz-Oro S. Acute exanthemas: a prospective study of 98 adult patients with an emphasis on cytokinic and metagenomic investigation. Br J Dermatol 2020;182:355-63. [PMID: 31127953 DOI: 10.1111/bjd.18166] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 1.7] [Reference Citation Analysis]
375 Aguirre de Cárcer D. Experimental and computational approaches to unravel microbial community assembly. Comput Struct Biotechnol J 2020;18:4071-81. [PMID: 33363703 DOI: 10.1016/j.csbj.2020.11.031] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
376 Huang L, Hong B, Yang W, Wang L, Yu R. Snipe: highly sensitive pathogen detection from metagenomic sequencing data. Brief Bioinform 2021:bbab064. [PMID: 33822895 DOI: 10.1093/bib/bbab064] [Reference Citation Analysis]
377 Bremges A, Fritz A, McHardy AC. CAMITAX: Taxon labels for microbial genomes. Gigascience 2020;9:giz154. [PMID: 31909794 DOI: 10.1093/gigascience/giz154] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
378 Li Y, Fu H, Yan D, Su X, Wang X, Zhao W, Wang H, Wang G. Effects of simulated surface freshwater environment on in situ microorganisms and their methanogenesis after tectonic uplift of a deep coal seam. International Journal of Coal Geology 2022. [DOI: 10.1016/j.coal.2022.104014] [Reference Citation Analysis]
379 Yang Q, Franco CMM, Zhang W. Uncovering the hidden marine sponge microbiome by applying a multi-primer approach. Sci Rep 2019;9:6214. [PMID: 30996336 DOI: 10.1038/s41598-019-42694-w] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.7] [Reference Citation Analysis]
380 Salerno C, Berardi G, Laera G, Pollice A. Functional Response of MBR Microbial Consortia to Substrate Stress as Revealed by Metaproteomics. Microb Ecol 2019;78:873-84. [DOI: 10.1007/s00248-019-01360-4] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
381 Hirano H, Takemoto K. Difficulty in inferring microbial community structure based on co-occurrence network approaches. BMC Bioinformatics 2019;20:329. [PMID: 31195956 DOI: 10.1186/s12859-019-2915-1] [Cited by in Crossref: 36] [Cited by in F6Publishing: 24] [Article Influence: 12.0] [Reference Citation Analysis]
382 Fang Y, Yuan Y, Liu J, Wu G, Yang J, Hua Z, Han J, Zhang X, Li W, Jiang H. Casting Light on the Adaptation Mechanisms and Evolutionary History of the Widespread Sumerlaeota. mBio 2021;12:e00350-21. [PMID: 33785617 DOI: 10.1128/mBio.00350-21] [Reference Citation Analysis]
383 Qi C, Wang P, Fu T, Lu M, Cai Y, Chen X, Cheng L. A comprehensive review for gut microbes: technologies, interventions, metabolites and diseases. Brief Funct Genomics 2021;20:42-60. [PMID: 33554248 DOI: 10.1093/bfgp/elaa029] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
384 Pérez-Burillo S, Molino S, Navajas-Porras B, Valverde-Moya ÁJ, Hinojosa-Nogueira D, López-Maldonado A, Pastoriza S, Rufián-Henares JÁ. An in vitro batch fermentation protocol for studying the contribution of food to gut microbiota composition and functionality. Nat Protoc 2021;16:3186-209. [PMID: 34089022 DOI: 10.1038/s41596-021-00537-x] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
385 Saenz C, Nigro E, Gunalan V, Arumugam M. MIntO: A Modular and Scalable Pipeline For Microbiome Metagenomic and Metatranscriptomic Data Integration. Front Bioinform 2022;2:846922. [DOI: 10.3389/fbinf.2022.846922] [Reference Citation Analysis]
386 Wang Y, Lyu N, Liu F, Liu WJ, Bi Y, Zhang Z, Ma S, Cao J, Song X, Wang A, Zhang G, Hu Y, Zhu B, Gao GF. More diversified antibiotic resistance genes in chickens and workers of the live poultry markets. Environ Int 2021;153:106534. [PMID: 33799229 DOI: 10.1016/j.envint.2021.106534] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
387 Grogan MD, Bartow-McKenney C, Flowers L, Knight SAB, Uberoi A, Grice EA. Research Techniques Made Simple: Profiling the Skin Microbiota. J Invest Dermatol 2019;139:747-752.e1. [PMID: 30904077 DOI: 10.1016/j.jid.2019.01.024] [Cited by in Crossref: 19] [Cited by in F6Publishing: 15] [Article Influence: 9.5] [Reference Citation Analysis]
388 Bekkers M, Stojkovic B, Kaiko GE. Mining the Microbiome and Microbiota-Derived Molecules in Inflammatory Bowel Disease. Int J Mol Sci 2021;22:11243. [PMID: 34681902 DOI: 10.3390/ijms222011243] [Reference Citation Analysis]
389 Li K, Lu Y, Deng L, Wang L, Shi L, Wang Z. Deconvolute individual genomes from metagenome sequences through short read clustering. PeerJ 2020;8:e8966. [PMID: 32296615 DOI: 10.7717/peerj.8966] [Cited by in Crossref: 4] [Article Influence: 2.0] [Reference Citation Analysis]
390 Xiong C, Singh BK, He JZ, Han YL, Li PP, Wan LH, Meng GZ, Liu SY, Wang JT, Wu CF, Ge AH, Zhang LM. Plant developmental stage drives the differentiation in ecological role of the maize microbiome. Microbiome 2021;9:171. [PMID: 34389047 DOI: 10.1186/s40168-021-01118-6] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
391 Mäklin T, Kallonen T, David S, Boinett CJ, Pascoe B, Méric G, Aanensen DM, Feil EJ, Baker S, Parkhill J, Sheppard SK, Corander J, Honkela A. High-resolution sweep metagenomics using fast probabilistic inference. Wellcome Open Res 2020;5:14. [DOI: 10.12688/wellcomeopenres.15639.1] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
392 Mäklin T, Kallonen T, David S, Boinett CJ, Pascoe B, Méric G, Aanensen DM, Feil EJ, Baker S, Parkhill J, Sheppard SK, Corander J, Honkela A. High-resolution sweep metagenomics using fast probabilistic inference. Wellcome Open Res 2020;5:14. [PMID: 34746439 DOI: 10.12688/wellcomeopenres.15639.2] [Reference Citation Analysis]
393 Chu J, Vila-Farres X, Brady SF. Bioactive Synthetic-Bioinformatic Natural Product Cyclic Peptides Inspired by Nonribosomal Peptide Synthetase Gene Clusters from the Human Microbiome. J Am Chem Soc 2019;141:15737-41. [PMID: 31545899 DOI: 10.1021/jacs.9b07317] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
394 DeWeese KJ, Osborne MG. Understanding the metabolome and metagenome as extended phenotypes: The next frontier in macroalgae domestication and improvement. J World Aquac Soc 2021;52:1009-30. [PMID: 34732977 DOI: 10.1111/jwas.12782] [Reference Citation Analysis]
395 Liu YX, Qin Y, Chen T, Lu M, Qian X, Guo X, Bai Y. A practical guide to amplicon and metagenomic analysis of microbiome data. Protein Cell 2021;12:315-30. [PMID: 32394199 DOI: 10.1007/s13238-020-00724-8] [Cited by in Crossref: 32] [Cited by in F6Publishing: 36] [Article Influence: 16.0] [Reference Citation Analysis]
396 Sedghi L, DiMassa V, Harrington A, Lynch SV, Kapila YL. The oral microbiome: Role of key organisms and complex networks in oral health and disease. Periodontol 2000 2021;87:107-31. [PMID: 34463991 DOI: 10.1111/prd.12393] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
397 D'Argenio V. Human Microbiome Acquisition and Bioinformatic Challenges in Metagenomic Studies. Int J Mol Sci 2018;19:E383. [PMID: 29382070 DOI: 10.3390/ijms19020383] [Cited by in Crossref: 25] [Cited by in F6Publishing: 22] [Article Influence: 6.3] [Reference Citation Analysis]
398 Chen C, Zhou Y, Fu H, Xiong X, Fang S, Jiang H, Wu J, Yang H, Gao J, Huang L. Expanded catalog of microbial genes and metagenome-assembled genomes from the pig gut microbiome. Nat Commun 2021;12:1106. [PMID: 33597514 DOI: 10.1038/s41467-021-21295-0] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 7.0] [Reference Citation Analysis]
399 Ko KKK, Chng KR, Nagarajan N. Metagenomics-enabled microbial surveillance. Nat Microbiol 2022;7:486-96. [PMID: 35365786 DOI: 10.1038/s41564-022-01089-w] [Reference Citation Analysis]
400 Riffle M, May DH, Timmins-Schiffman E, Mikan MP, Jaschob D, Noble WS, Nunn BL. MetaGOmics: A Web-Based Tool for Peptide-Centric Functional and Taxonomic Analysis of Metaproteomics Data. Proteomes 2017;6:E2. [PMID: 29280960 DOI: 10.3390/proteomes6010002] [Cited by in Crossref: 29] [Cited by in F6Publishing: 23] [Article Influence: 5.8] [Reference Citation Analysis]
401 Ishida N, Kawano Y, Fukui R, Zhang M, Tashiro Y, Sakai K. Clarification of the Dynamic Autothermal Thermophilic Aerobic Digestion Process Using Metagenomic Analysis. Microbiol Spectr 2022;:e0056122. [PMID: 35348372 DOI: 10.1128/spectrum.00561-22] [Reference Citation Analysis]
402 Gogolev YV, Ahmar S, Akpinar BA, Budak H, Kiryushkin AS, Gorshkov VY, Hensel G, Demchenko KN, Kovalchuk I, Mora-Poblete F, Muslu T, Tsers ID, Yadav NS, Korzun V. OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security. Plants (Basel) 2021;10:1423. [PMID: 34371624 DOI: 10.3390/plants10071423] [Reference Citation Analysis]
403 Kwun JS, Kang SH, Lee HJ, Park HK, Lee WJ, Yoon CH, Suh JW, Cho YS, Youn TJ, Chae IH. Comparison of thrombus, gut, and oral microbiomes in Korean patients with ST-elevation myocardial infarction: a case-control study. Exp Mol Med 2020;52:2069-79. [PMID: 33339953 DOI: 10.1038/s12276-020-00543-1] [Reference Citation Analysis]
404 Silva JP, Ticona ARP, Hamann PRV, Quirino BF, Noronha EF. Deconstruction of Lignin: From Enzymes to Microorganisms. Molecules 2021;26:2299. [PMID: 33921125 DOI: 10.3390/molecules26082299] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
405 Utter DR, Borisy GG, Eren AM, Cavanaugh CM, Mark Welch JL. Metapangenomics of the oral microbiome provides insights into habitat adaptation and cultivar diversity. Genome Biol 2020;21:293. [PMID: 33323129 DOI: 10.1186/s13059-020-02200-2] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
406 Brandt C, Bongcam-rudloff E, Müller B. Abundance Tracking by Long-Read Nanopore Sequencing of Complex Microbial Communities in Samples from 20 Different Biogas/Wastewater Plants. Applied Sciences 2020;10:7518. [DOI: 10.3390/app10217518] [Cited by in Crossref: 7] [Cited by in F6Publishing: 1] [Article Influence: 3.5] [Reference Citation Analysis]
407 Čoklo M, Maslov DR, Kraljević Pavelić S. Modulation of gut microbiota in healthy rats after exposure to nutritional supplements. Gut Microbes 2020;12:1-28. [PMID: 32845788 DOI: 10.1080/19490976.2020.1779002] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
408 Moran-Gilad J. How do advanced diagnostics support public health policy development? Euro Surveill 2019;24. [PMID: 30696524 DOI: 10.2807/1560-7917.ES.2019.24.4.1900068] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 3.5] [Reference Citation Analysis]
409 Nicholls SM, Quick JC, Tang S, Loman NJ. Ultra-deep, long-read nanopore sequencing of mock microbial community standards. Gigascience 2019;8:giz043. [PMID: 31089679 DOI: 10.1093/gigascience/giz043] [Cited by in Crossref: 106] [Cited by in F6Publishing: 68] [Article Influence: 35.3] [Reference Citation Analysis]
410 Qian XB, Chen T, Xu YP, Chen L, Sun FX, Lu MP, Liu YX. A guide to human microbiome research: study design, sample collection, and bioinformatics analysis. Chin Med J (Engl) 2020;133:1844-55. [PMID: 32604176 DOI: 10.1097/CM9.0000000000000871] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
411 Sorbie A, Delgado Jiménez R, Benakis C. Increasing transparency and reproducibility in stroke-microbiota research: A toolbox for microbiota analysis. iScience 2022;25:103998. [DOI: 10.1016/j.isci.2022.103998] [Reference Citation Analysis]
412 Fritz A, Hofmann P, Majda S, Dahms E, Dröge J, Fiedler J, Lesker TR, Belmann P, DeMaere MZ, Darling AE, Sczyrba A, Bremges A, McHardy AC. CAMISIM: simulating metagenomes and microbial communities. Microbiome 2019;7:17. [PMID: 30736849 DOI: 10.1186/s40168-019-0633-6] [Cited by in Crossref: 42] [Cited by in F6Publishing: 31] [Article Influence: 14.0] [Reference Citation Analysis]
413 Yue Y, Huang H, Qi Z, Dou HM, Liu XY, Han TF, Chen Y, Song XJ, Zhang YH, Tu J. Evaluating metagenomics tools for genome binning with real metagenomic datasets and CAMI datasets. BMC Bioinformatics 2020;21:334. [PMID: 32723290 DOI: 10.1186/s12859-020-03667-3] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 5.0] [Reference Citation Analysis]
414 Mbareche H, Veillette M, Bilodeau G, Duchaine C. Comparison of the performance of ITS1 and ITS2 as barcodes in amplicon-based sequencing of bioaerosols. PeerJ 2020;8:e8523. [PMID: 32110484 DOI: 10.7717/peerj.8523] [Cited by in Crossref: 15] [Cited by in F6Publishing: 9] [Article Influence: 7.5] [Reference Citation Analysis]
415 Ditz B, Christenson S, Rossen J, Brightling C, Kerstjens HAM, van den Berge M, Faiz A. Sputum microbiome profiling in COPD: beyond singular pathogen detection. Thorax 2020;75:338-44. [PMID: 31996401 DOI: 10.1136/thoraxjnl-2019-214168] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
416 Song H, Lim Y, Im H, Bae JM, Kang GH, Ahn J, Baek D, Kim TY, Yoon SS, Koh Y. Interpretation of EBV infection in pan-cancer genome considering viral life cycle: LiEB (Life cycle of Epstein-Barr virus). Sci Rep 2019;9:3465. [PMID: 30837539 DOI: 10.1038/s41598-019-39706-0] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
417 Teitelbaum CS, Amoroso CR, Huang S, Davies TJ, Rushmore J, Drake JM, Stephens PR, Byers JE, Majewska AA, Nunn CL. A comparison of diversity estimators applied to a database of host–parasite associations. Ecography 2020;43:1316-28. [DOI: 10.1111/ecog.05143] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
418 Bharti R, Grimm DG. Current challenges and best-practice protocols for microbiome analysis. Brief Bioinform 2021;22:178-93. [PMID: 31848574 DOI: 10.1093/bib/bbz155] [Cited by in Crossref: 41] [Cited by in F6Publishing: 35] [Article Influence: 13.7] [Reference Citation Analysis]
419 Ahannach S, Spacova I, Decorte R, Jehaes E, Lebeer S. At the Interface of Life and Death: Post-mortem and Other Applications of Vaginal, Skin, and Salivary Microbiome Analysis in Forensics. Front Microbiol 2021;12:694447. [PMID: 34394033 DOI: 10.3389/fmicb.2021.694447] [Reference Citation Analysis]
420 Shen M, Li Q, Ren M, Lin Y, Wang J, Chen L, Li T, Zhao J. Trophic Status Is Associated With Community Structure and Metabolic Potential of Planktonic Microbiota in Plateau Lakes. Front Microbiol 2019;10:2560. [PMID: 31787952 DOI: 10.3389/fmicb.2019.02560] [Cited by in Crossref: 11] [Cited by in F6Publishing: 6] [Article Influence: 3.7] [Reference Citation Analysis]
421 Murphy TR, Xiao R, Hamilton-Brehm SD. Hybrid genome de novo assembly with methylome analysis of the anaerobic thermophilic subsurface bacterium Thermanaerosceptrum fracticalcis strain DRI-13T. BMC Genomics 2021;22:209. [PMID: 33757423 DOI: 10.1186/s12864-021-07535-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
422 Handy SM, Pawar RS, Ottesen AR, Ramachandran P, Sagi S, Zhang N, Hsu E, Erickson DL. HPLC-UV, Metabarcoding and Genome Skims of Botanical Dietary Supplements: A Case Study in Echinacea. Planta Med 2021;87:314-24. [PMID: 33445185 DOI: 10.1055/a-1336-1685] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
423 Spacova I, Dodiya HB, Happel AU, Strain C, Vandenheuvel D, Wang X, Reid G. Future of Probiotics and Prebiotics and the Implications for Early Career Researchers. Front Microbiol 2020;11:1400. [PMID: 32714306 DOI: 10.3389/fmicb.2020.01400] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
424 Gilliot P, Gorochowski TE. Sequencing enabling design and learning in synthetic biology. Current Opinion in Chemical Biology 2020;58:54-62. [DOI: 10.1016/j.cbpa.2020.06.002] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
425 Jo J, Oh J, Park C. Microbial community analysis using high-throughput sequencing technology: a beginner's guide for microbiologists. J Microbiol 2020;58:176-92. [PMID: 32108314 DOI: 10.1007/s12275-020-9525-5] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
426 Houlihan CF, Bharucha T, Breuer J. Advances in molecular diagnostic testing for central nervous system infections. Curr Opin Infect Dis 2019;32:244-50. [PMID: 30950854 DOI: 10.1097/QCO.0000000000000548] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
427 Marre S, Gasc C, Forest C, Lebbaoui Y, Mosoni P, Peyret P. Revealing microbial species diversity using sequence capture by hybridization. Microb Genom 2021;7. [PMID: 34882529 DOI: 10.1099/mgen.0.000714] [Reference Citation Analysis]
428 Gamie Z, Karthikappallil D, Gamie E, Stamiris S, Kenanidis E, Tsiridis E. Molecular sequencing technologies in the diagnosis and management of prosthetic joint infections. Expert Rev Mol Diagn 2021;:1-21. [PMID: 33641572 DOI: 10.1080/14737159.2021.1894929] [Reference Citation Analysis]
429 Ho M, Moon D, Pires-Alves M, Thornton PD, McFarlin BL, Wilson BA. Recovery of microbial community profile information hidden in chimeric sequence reads. Comput Struct Biotechnol J 2021;19:5126-39. [PMID: 34589188 DOI: 10.1016/j.csbj.2021.08.050] [Reference Citation Analysis]
430 Hu Y, Fang L, Nicholson C, Wang K. Implications of Error-Prone Long-Read Whole-Genome Shotgun Sequencing on Characterizing Reference Microbiomes. iScience 2020;23:101223. [PMID: 32563152 DOI: 10.1016/j.isci.2020.101223] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
431 Brandi G, Frega G. Microbiota: Overview and Implication in Immunotherapy-Based Cancer Treatments. Int J Mol Sci 2019;20:E2699. [PMID: 31159348 DOI: 10.3390/ijms20112699] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 4.7] [Reference Citation Analysis]
432 Ferretti P, Pasolli E, Tett A, Asnicar F, Gorfer V, Fedi S, Armanini F, Truong DT, Manara S, Zolfo M, Beghini F, Bertorelli R, De Sanctis V, Bariletti I, Canto R, Clementi R, Cologna M, Crifò T, Cusumano G, Gottardi S, Innamorati C, Masè C, Postai D, Savoi D, Duranti S, Lugli GA, Mancabelli L, Turroni F, Ferrario C, Milani C, Mangifesta M, Anzalone R, Viappiani A, Yassour M, Vlamakis H, Xavier R, Collado CM, Koren O, Tateo S, Soffiati M, Pedrotti A, Ventura M, Huttenhower C, Bork P, Segata N. Mother-to-Infant Microbial Transmission from Different Body Sites Shapes the Developing Infant Gut Microbiome. Cell Host Microbe 2018;24:133-145.e5. [PMID: 30001516 DOI: 10.1016/j.chom.2018.06.005] [Cited by in Crossref: 325] [Cited by in F6Publishing: 287] [Article Influence: 108.3] [Reference Citation Analysis]
433 Sharpton SR, Yong GJM, Terrault NA, Lynch SV. Gut Microbial Metabolism and Nonalcoholic Fatty Liver Disease. Hepatol Commun 2019;3:29-43. [PMID: 30619992 DOI: 10.1002/hep4.1284] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 2.5] [Reference Citation Analysis]
434 Almeida OGG, De Martinis ECP. Bioinformatics tools to assess metagenomic data for applied microbiology. Appl Microbiol Biotechnol 2019;103:69-82. [DOI: 10.1007/s00253-018-9464-9] [Cited by in Crossref: 20] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
435 Schlaberg R. Microbiome Diagnostics. Clin Chem 2020;66:68-76. [PMID: 31843867 DOI: 10.1373/clinchem.2019.303248] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 3.5] [Reference Citation Analysis]
436 Zimmermann J, Kaleta C, Waschina S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 2021;22:81. [PMID: 33691770 DOI: 10.1186/s13059-021-02295-1] [Cited by in Crossref: 3] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
437 Liu HH, Lin YC, Chung CS, Liu K, Chang YH, Yang CH, Chen Y, Ni YH, Chang PF. Integrated Counts of Carbohydrate-Active Protein Domains as Metabolic Readouts to Distinguish Probiotic Biology and Human Fecal Metagenomes. Sci Rep 2019;9:16836. [PMID: 31727954 DOI: 10.1038/s41598-019-53173-7] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
438 Ciuffreda L, Rodríguez-Pérez H, Flores C. Nanopore sequencing and its application to the study of microbial communities. Comput Struct Biotechnol J 2021;19:1497-511. [PMID: 33815688 DOI: 10.1016/j.csbj.2021.02.020] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
439 Beck LC, Granger CL, Masi AC, Stewart CJ. Use of omic technologies in early life gastrointestinal health and disease: from bench to bedside. Expert Rev Proteomics 2021;18:247-59. [PMID: 33896313 DOI: 10.1080/14789450.2021.1922278] [Reference Citation Analysis]
440 Kawulok J, Kawulok M, Deorowicz S. Environmental metagenome classification for constructing a microbiome fingerprint. Biol Direct 2019;14:20. [PMID: 31722729 DOI: 10.1186/s13062-019-0251-z] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
441 Ghensi P, Manghi P, Zolfo M, Armanini F, Pasolli E, Bolzan M, Bertelle A, Dell'Acqua F, Dellasega E, Waldner R, Tessarolo F, Tomasi C, Segata N. Strong oral plaque microbiome signatures for dental implant diseases identified by strain-resolution metagenomics. NPJ Biofilms Microbiomes 2020;6:47. [PMID: 33127901 DOI: 10.1038/s41522-020-00155-7] [Cited by in Crossref: 8] [Cited by in F6Publishing: 10] [Article Influence: 4.0] [Reference Citation Analysis]
442 Li Y, Jin Y, Zhang J, Pan H, Wu L, Liu D, Liu J, Hu J, Shen J. Recovery of human gut microbiota genomes with third-generation sequencing. Cell Death Dis 2021;12:569. [PMID: 34078878 DOI: 10.1038/s41419-021-03829-y] [Reference Citation Analysis]
443 Gastélum G, Rocha J. La milpa como modelo para el estudio de la microbiodiversidad e interacciones planta-bacteria. TIP RECQB 2020;23. [DOI: 10.22201/fesz.23958723e.2020.0.254] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
444 Yi M, Yu S, Qin S, Liu Q, Xu H, Zhao W, Chu Q, Wu K. Gut microbiome modulates efficacy of immune checkpoint inhibitors. J Hematol Oncol. 2018;11:47. [PMID: 29580257 DOI: 10.1186/s13045-018-0592-6] [Cited by in Crossref: 65] [Cited by in F6Publishing: 65] [Article Influence: 16.3] [Reference Citation Analysis]
445 Xu P, Modavi C, Demaree B, Twigg F, Liang B, Sun C, Zhang W, Abate AR. Microfluidic automated plasmid library enrichment for biosynthetic gene cluster discovery. Nucleic Acids Res 2020;48:e48. [PMID: 32095820 DOI: 10.1093/nar/gkaa131] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 3.5] [Reference Citation Analysis]
446 Easterly CW, Sajulga R, Mehta S, Johnson J, Kumar P, Hubler S, Mesuere B, Rudney J, Griffin TJ, Jagtap PD. metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes. Mol Cell Proteomics 2019;18:S82-91. [PMID: 31235611 DOI: 10.1074/mcp.RA118.001240] [Cited by in Crossref: 18] [Cited by in F6Publishing: 9] [Article Influence: 6.0] [Reference Citation Analysis]
447 Zhou W, Bian Y. Thanatomicrobiome composition profiling as a tool for forensic investigation. Forensic Sci Res 2018;3:105-10. [PMID: 30483658 DOI: 10.1080/20961790.2018.1466430] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 2.5] [Reference Citation Analysis]
448 Park J, Wang HH. Systematic and synthetic approaches to rewire regulatory networks. Curr Opin Syst Biol 2018;8:90-6. [PMID: 30637352 DOI: 10.1016/j.coisb.2017.12.009] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
449 Doane MP, Johnson CJ, Johri S, Kerr EN, Morris MM, Desantiago R, Turnlund AC, Goodman A, Mora M, Lima LFO, Nosal AP, Dinsdale EA. The Epidermal Microbiome Within an Aggregation of Leopard Sharks (Triakis semifasciata) Has Taxonomic Flexibility with Gene Functional Stability Across Three Time-points. Microb Ecol 2022. [PMID: 35129649 DOI: 10.1007/s00248-022-01969-y] [Reference Citation Analysis]
450 Pierce MP. Filling in the Gaps: Adopting Ultraconserved Elements Alongside COI to Strengthen Metabarcoding Studies. Front Ecol Evol 2019;7:469. [DOI: 10.3389/fevo.2019.00469] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
451 Van Rossum T, Ferretti P, Maistrenko OM, Bork P. Diversity within species: interpreting strains in microbiomes. Nat Rev Microbiol 2020;18:491-506. [PMID: 32499497 DOI: 10.1038/s41579-020-0368-1] [Cited by in Crossref: 52] [Cited by in F6Publishing: 38] [Article Influence: 26.0] [Reference Citation Analysis]
452 Grossart H, Massana R, Mcmahon KD, Walsh DA. Linking metagenomics to aquatic microbial ecology and biogeochemical cycles. Limnol Oceanogr 2020;65. [DOI: 10.1002/lno.11382] [Cited by in Crossref: 21] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
453 Melkonian C, Gottstein W, Blasche S, Kim Y, Abel-Kistrup M, Swiegers H, Saerens S, Edwards N, Patil KR, Teusink B, Molenaar D. Finding Functional Differences Between Species in a Microbial Community: Case Studies in Wine Fermentation and Kefir Culture. Front Microbiol 2019;10:1347. [PMID: 31293529 DOI: 10.3389/fmicb.2019.01347] [Cited by in Crossref: 112] [Cited by in F6Publishing: 8] [Article Influence: 37.3] [Reference Citation Analysis]
454 Pereira-Marques J, Ferreira RM, Machado JC, Figueiredo C. The influence of the gastric microbiota in gastric cancer development. Best Pract Res Clin Gastroenterol 2021;50-51:101734. [PMID: 33975676 DOI: 10.1016/j.bpg.2021.101734] [Reference Citation Analysis]
455 Vida A, Kardos G, Kovács T, Bodrogi BL, Bai P. Deletion of poly(ADP‑ribose) polymerase-1 changes the composition of the microbiome in the gut. Mol Med Rep 2018;18:4335-41. [PMID: 30221733 DOI: 10.3892/mmr.2018.9474] [Cited by in Crossref: 2] [Cited by in F6Publishing: 9] [Article Influence: 0.5] [Reference Citation Analysis]
456 Nagpal S, Haque MM, Singh R, Mande SS. iVikodak-A Platform and Standard Workflow for Inferring, Analyzing, Comparing, and Visualizing the Functional Potential of Microbial Communities. Front Microbiol 2018;9:3336. [PMID: 30692979 DOI: 10.3389/fmicb.2018.03336] [Cited by in Crossref: 23] [Cited by in F6Publishing: 16] [Article Influence: 7.7] [Reference Citation Analysis]
457 Pedersen HK, Forslund SK, Gudmundsdottir V, Petersen AØ, Hildebrand F, Hyötyläinen T, Nielsen T, Hansen T, Bork P, Ehrlich SD, Brunak S, Oresic M, Pedersen O, Nielsen HB. A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links. Nat Protoc 2018;13:2781-800. [DOI: 10.1038/s41596-018-0064-z] [Cited by in Crossref: 35] [Cited by in F6Publishing: 29] [Article Influence: 8.8] [Reference Citation Analysis]
458 Macher JN, Wideman JG, Girard EB, Langerak A, Duijm E, Jompa J, Sadekov A, Vos R, Wissels R, Renema W. First report of mitochondrial COI in foraminifera and implications for DNA barcoding. Sci Rep 2021;11:22165. [PMID: 34772985 DOI: 10.1038/s41598-021-01589-5] [Reference Citation Analysis]
459 Góes-Neto A, Kukharenko O, Orlovska I, Podolich O, Imchen M, Kumavath R, Kato RB, de Carvalho DS, Tiwari S, Brenig B, Azevedo V, Reva O, de Vera JP, Kozyrovska N, Barh D. Shotgun metagenomic analysis of kombucha mutualistic community exposed to Mars-like environment outside the International Space Station. Environ Microbiol 2021;23:3727-42. [PMID: 33476085 DOI: 10.1111/1462-2920.15405] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
460 Ong CT, Turni C, Blackall PJ, Boe-Hansen G, Hayes BJ, Tabor AE. Interrogating the bovine reproductive tract metagenomes using culture-independent approaches: a systematic review. Anim Microbiome 2021;3:41. [PMID: 34108039 DOI: 10.1186/s42523-021-00106-3] [Reference Citation Analysis]
461 Liu S, Wang H, Chen L, Wang J, Zheng M, Liu S, Chen Q, Ni J. Comammox Nitrospira within the Yangtze River continuum: community, biogeography, and ecological drivers. ISME J 2020;14:2488-504. [PMID: 32555502 DOI: 10.1038/s41396-020-0701-8] [Cited by in Crossref: 21] [Cited by in F6Publishing: 15] [Article Influence: 10.5] [Reference Citation Analysis]
462 Diwan AD, Harke SN, Gopalkrishna, Panche AN. Aquaculture industry prospective from gut microbiome of fish and shellfish: An overview. J Anim Physiol Anim Nutr (Berl) 2021. [PMID: 34355428 DOI: 10.1111/jpn.13619] [Reference Citation Analysis]
463 Tümmler B. Molecular epidemiology in current times. Environ Microbiol 2020;22:4909-18. [PMID: 32945108 DOI: 10.1111/1462-2920.15238] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
464 Kang Y, Zhang H, Hu M, Ma Y, Chen P, Zhao Z, Li J, Ye Y, Zheng M, Lou Y. Alterations in the Ocular Surface Microbiome in Traumatic Corneal Ulcer Patients. Invest Ophthalmol Vis Sci 2020;61:35. [PMID: 32543662 DOI: 10.1167/iovs.61.6.35] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
465 Mohr AE, Gumpricht E, Sears DD, Sweazea KL. Recent advances and health implications of dietary fasting regimens on the gut microbiome. Am J Physiol Gastrointest Liver Physiol 2021;320:G847-63. [PMID: 33729005 DOI: 10.1152/ajpgi.00475.2020] [Reference Citation Analysis]
466 Shean RC, Greninger AL. One future of clinical metagenomic sequencing for infectious diseases. Expert Rev Mol Diagn 2019;19:849-51. [PMID: 31426667 DOI: 10.1080/14737159.2019.1658524] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
467 Nissen JN, Johansen J, Allesøe RL, Sønderby CK, Armenteros JJA, Grønbech CH, Jensen LJ, Nielsen HB, Petersen TN, Winther O, Rasmussen S. Improved metagenome binning and assembly using deep variational autoencoders. Nat Biotechnol 2021;39:555-60. [PMID: 33398153 DOI: 10.1038/s41587-020-00777-4] [Cited by in Crossref: 14] [Cited by in F6Publishing: 2] [Article Influence: 14.0] [Reference Citation Analysis]
468 Swann JR, Rajilic-Stojanovic M, Salonen A, Sakwinska O, Gill C, Meynier A, Fança-Berthon P, Schelkle B, Segata N, Shortt C, Tuohy K, Hasselwander O. Considerations for the design and conduct of human gut microbiota intervention studies relating to foods. Eur J Nutr 2020;59:3347-68. [PMID: 32246263 DOI: 10.1007/s00394-020-02232-1] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
469 Brown CT, Moritz D, O'Brien MP, Reidl F, Reiter T, Sullivan BD. Exploring neighborhoods in large metagenome assembly graphs using spacegraphcats reveals hidden sequence diversity. Genome Biol 2020;21:164. [PMID: 32631445 DOI: 10.1186/s13059-020-02066-4] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 4.5] [Reference Citation Analysis]
470 Laudadio I, Fulci V, Stronati L, Carissimi C. Next-Generation Metagenomics: Methodological Challenges and Opportunities. OMICS 2019;23:327-33. [PMID: 31188063 DOI: 10.1089/omi.2019.0073] [Cited by in Crossref: 17] [Cited by in F6Publishing: 15] [Article Influence: 5.7] [Reference Citation Analysis]
471 Serrano D, Pozzi C, Guglietta S, Fosso B, Suppa M, Gnagnarella P, Corso F, Bellerba F, Macis D, Aristarco V, Manghi P, Segata N, Trovato C, Zampino MG, Marzano M, Bonanni B, Rescigno M, Gandini S. Microbiome as Mediator of Diet on Colorectal Cancer Risk: The Role of Vitamin D, Markers of Inflammation and Adipokines. Nutrients 2021;13:363. [PMID: 33504116 DOI: 10.3390/nu13020363] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
472 Dos Santos DG, Coelho CCS, Ferreira ABR, Freitas-Silva O. Brazilian Coffee Production and the Future Microbiome and Mycotoxin Profile Considering the Climate Change Scenario. Microorganisms 2021;9:858. [PMID: 33923588 DOI: 10.3390/microorganisms9040858] [Reference Citation Analysis]
473 Magesh S, Jonsson V, Bengtsson-palme J. Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data. MBMG 2019;3:e36236. [DOI: 10.3897/mbmg.3.36236] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.7] [Reference Citation Analysis]