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For: Groza T, Köhler S, Moldenhauer D, Vasilevsky N, Baynam G, Zemojtel T, Schriml LM, Kibbe WA, Schofield PN, Beck T, Vasant D, Brookes AJ, Zankl A, Washington NL, Mungall CJ, Lewis SE, Haendel MA, Parkinson H, Robinson PN. The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease. Am J Hum Genet 2015;97:111-24. [PMID: 26119816 DOI: 10.1016/j.ajhg.2015.05.020] [Cited by in Crossref: 152] [Cited by in F6Publishing: 116] [Article Influence: 21.7] [Reference Citation Analysis]
Number Citing Articles
1 Lupski JR. Clan genomics: From OMIM phenotypic traits to genes and biology. Am J Med Genet A 2021;185:3294-313. [PMID: 34405553 DOI: 10.1002/ajmg.a.62434] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
2 Álvaro-Sánchez S, Abreu-Rodríguez I, Abulí A, Serra-Juhe C, Garrido-Navas MDC. Current Status of Genetic Counselling for Rare Diseases in Spain. Diagnostics (Basel) 2021;11:2320. [PMID: 34943558 DOI: 10.3390/diagnostics11122320] [Reference Citation Analysis]
3 Haghighi A, Krier JB, Toth-Petroczy A, Cassa CA, Frank NY, Carmichael N, Fieg E, Bjonnes A, Mohanty A, Briere LC, Lincoln S, Lucia S, Gupta VA, Söylemez O, Sutti S, Kooshesh K, Qiu H, Fay CJ, Perroni V, Valerius J, Hanna M, Frank A, Ouahed J, Snapper SB, Pantazi A, Chopra SS, Leshchiner I, Stitziel NO, Feldweg A, Mannstadt M, Loscalzo J, Sweetser DA, Liao E, Stoler JM, Nowak CB, Sanchez-Lara PA, Klein OD, Perry H, Patsopoulos NA, Raychaudhuri S, Goessling W, Green RC, Seidman CE, MacRae CA, Sunyaev SR, Maas RL, Vuzman D; Undiagnosed Diseases Network, Brigham and Women’s Hospital FaceBase Project, Brigham Genomic Medicine (BGM). An integrated clinical program and crowdsourcing strategy for genomic sequencing and Mendelian disease gene discovery. NPJ Genom Med 2018;3:21. [PMID: 30131872 DOI: 10.1038/s41525-018-0060-9] [Cited by in Crossref: 17] [Cited by in F6Publishing: 11] [Article Influence: 4.3] [Reference Citation Analysis]
4 Tumienė B, Maver A, Writzl K, Hodžić A, Čuturilo G, Kuzmanić-Šamija R, Čulić V, Peterlin B. Diagnostic exome sequencing of syndromic epilepsy patients in clinical practice. Clin Genet 2018;93:1057-62. [PMID: 29286531 DOI: 10.1111/cge.13203] [Cited by in Crossref: 21] [Cited by in F6Publishing: 17] [Article Influence: 5.3] [Reference Citation Analysis]
5 Liu L, Huang X, Mamitsuka H, Zhu S, Wren J. HPOLabeler: improving prediction of human protein–phenotype associations by learning to rank. Bioinformatics 2020;36:4180-8. [DOI: 10.1093/bioinformatics/btaa284] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
6 Zolotareva O, Kleine M. A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases. J Integr Bioinform 2019;16:/j/jib. [PMID: 31494632 DOI: 10.1515/jib-2018-0069] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 1.7] [Reference Citation Analysis]
7 Tan TY, Gonzaga-Jauregui C, Bhoj EJ, Strauss KA, Brigatti K, Puffenberger E, Li D, Xie L, Das N, Skubas I, Deckelbaum RA, Hughes V, Brydges S, Hatsell S, Siao CJ, Dominguez MG, Economides A, Overton JD, Mayne V, Simm PJ, Jones BO, Eggers S, Le Guyader G, Pelluard F, Haack TB, Sturm M, Riess A, Waldmueller S, Hofbeck M, Steindl K, Joset P, Rauch A, Hakonarson H, Baker NL, Farlie PG. Monoallelic BMP2 Variants Predicted to Result in Haploinsufficiency Cause Craniofacial, Skeletal, and Cardiac Features Overlapping Those of 20p12 Deletions. Am J Hum Genet 2017;101:985-94. [PMID: 29198724 DOI: 10.1016/j.ajhg.2017.10.006] [Cited by in Crossref: 34] [Cited by in F6Publishing: 23] [Article Influence: 6.8] [Reference Citation Analysis]
8 International Society for Biocuration. Biocuration: Distilling data into knowledge. PLoS Biol 2018;16:e2002846. [PMID: 29659566 DOI: 10.1371/journal.pbio.2002846] [Cited by in Crossref: 35] [Cited by in F6Publishing: 25] [Article Influence: 8.8] [Reference Citation Analysis]
9 Barros M, Couto FM. Knowledge Representation and Management: a Linked Data Perspective. Yearb Med Inform 2016;:178-83. [PMID: 27830248 DOI: 10.15265/IY-2016-022] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 1.5] [Reference Citation Analysis]
10 Finke MT, Filice RW, Kahn CE Jr. Integrating ontologies of human diseases, phenotypes, and radiological diagnosis. J Am Med Inform Assoc 2019;26:149-54. [PMID: 30624645 DOI: 10.1093/jamia/ocy161] [Cited by in Crossref: 3] [Article Influence: 1.0] [Reference Citation Analysis]
11 Macnamara EF, D'Souza P, Tifft CJ; Undiagnosed Diseases Network. The undiagnosed diseases program: Approach to diagnosis. Transl Sci Rare Dis 2020;4:179-88. [PMID: 32477883 DOI: 10.3233/TRD-190045] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Trinh J, Imhoff S, Dulovic-Mahlow M, Kandaswamy KK, Tadic V, Schäfer J, Dobricic V, Nolte A, Werber M, Rolfs A, Münchau A, Klein C, Lohmann K, Brüggemann N. Novel NAXE variants as a cause for neurometabolic disorder: implications for treatment. J Neurol 2020;267:770-82. [PMID: 31745726 DOI: 10.1007/s00415-019-09640-2] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 2.7] [Reference Citation Analysis]
13 Peng J, Li Q, Shang X. Investigations on factors influencing HPO-based semantic similarity calculation. J Biomed Semantics 2017;8:34. [PMID: 29297376 DOI: 10.1186/s13326-017-0144-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.4] [Reference Citation Analysis]
14 Subirats L, Conesa J, Armayones M. Biomedical Holistic Ontology for People with Rare Diseases. Int J Environ Res Public Health 2020;17:E6038. [PMID: 32825147 DOI: 10.3390/ijerph17176038] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
15 Bush WS, Oetjens MT, Crawford DC. Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet 2016;17:129-45. [PMID: 26875678 DOI: 10.1038/nrg.2015.36] [Cited by in Crossref: 151] [Cited by in F6Publishing: 122] [Article Influence: 25.2] [Reference Citation Analysis]
16 Acuna-Hidalgo R, Veltman JA, Hoischen A. New insights into the generation and role of de novo mutations in health and disease. Genome Biol 2016;17:241. [PMID: 27894357 DOI: 10.1186/s13059-016-1110-1] [Cited by in Crossref: 204] [Cited by in F6Publishing: 149] [Article Influence: 34.0] [Reference Citation Analysis]
17 Köhler S, Vasilevsky NA, Engelstad M, Foster E, McMurry J, Aymé S, Baynam G, Bello SM, Boerkoel CF, Boycott KM, Brudno M, Buske OJ, Chinnery PF, Cipriani V, Connell LE, Dawkins HJ, DeMare LE, Devereau AD, de Vries BB, Firth HV, Freson K, Greene D, Hamosh A, Helbig I, Hum C, Jähn JA, James R, Krause R, F Laulederkind SJ, Lochmüller H, Lyon GJ, Ogishima S, Olry A, Ouwehand WH, Pontikos N, Rath A, Schaefer F, Scott RH, Segal M, Sergouniotis PI, Sever R, Smith CL, Straub V, Thompson R, Turner C, Turro E, Veltman MW, Vulliamy T, Yu J, von Ziegenweidt J, Zankl A, Züchner S, Zemojtel T, Jacobsen JO, Groza T, Smedley D, Mungall CJ, Haendel M, Robinson PN. The Human Phenotype Ontology in 2017. Nucleic Acids Res 2017;45:D865-76. [PMID: 27899602 DOI: 10.1093/nar/gkw1039] [Cited by in Crossref: 470] [Cited by in F6Publishing: 376] [Article Influence: 78.3] [Reference Citation Analysis]
18 Han SK, Kong J, Kim S, Lee JH, Han DH. Exomic and transcriptomic alterations of hereditary gingival fibromatosis. Oral Dis 2019;25:1374-83. [PMID: 30907493 DOI: 10.1111/odi.13093] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.7] [Reference Citation Analysis]
19 Lin FP, Groza T, Kocbek S, Antezana E, Epstein RJ. Cancer Care Treatment Outcome Ontology: A Novel Computable Ontology for Profiling Treatment Outcomes in Patients With Solid Tumors. JCO Clin Cancer Inform 2018;2:1-14. [PMID: 30652600 DOI: 10.1200/CCI.18.00026] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
20 Stamouli S, Anderlid B, Willfors C, Thiruvahindrapuram B, Wei J, Berggren S, Nordgren A, Scherer SW, Lichtenstein P, Tammimies K, Bölte S. Copy Number Variation Analysis of 100 Twin Pairs Enriched for Neurodevelopmental Disorders. Twin Res Hum Genet 2018;21:1-11. [DOI: 10.1017/thg.2017.69] [Cited by in Crossref: 17] [Cited by in F6Publishing: 13] [Article Influence: 4.3] [Reference Citation Analysis]
21 de La Dure-Molla M, Fournier BP, Manzanares MC, Acevedo AC, Hennekam RC, Friedlander L, Boy-Lefèvre ML, Kerner S, Toupenay S, Garrec P, Vi-Fane B, Felizardo R, Berteretche MV, Jordan L, Ferré F, Clauss F, Jung S, de Chalendar M, Troester S, Kawczynski M, Chaloyard J, Manière MC, Berdal A, Bloch-Zupan A; International Group of Dental Nomenclature. Elements of morphology: Standard terminology for the teeth and classifying genetic dental disorders. Am J Med Genet A 2019;179:1913-81. [PMID: 31468724 DOI: 10.1002/ajmg.a.61316] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 2.3] [Reference Citation Analysis]
22 Shimoyama M, Laulederkind SJ, De Pons J, Nigam R, Smith JR, Tutaj M, Petri V, Hayman GT, Wang SJ, Ghiasvand O, Thota J, Dwinell MR. Exploring human disease using the Rat Genome Database. Dis Model Mech 2016;9:1089-95. [PMID: 27736745 DOI: 10.1242/dmm.026021] [Cited by in Crossref: 23] [Cited by in F6Publishing: 20] [Article Influence: 4.6] [Reference Citation Analysis]
23 Mungall CJ, McMurry JA, Köhler S, Balhoff JP, Borromeo C, Brush M, Carbon S, Conlin T, Dunn N, Engelstad M, Foster E, Gourdine JP, Jacobsen JO, Keith D, Laraway B, Lewis SE, NguyenXuan J, Shefchek K, Vasilevsky N, Yuan Z, Washington N, Hochheiser H, Groza T, Smedley D, Robinson PN, Haendel MA. The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species. Nucleic Acids Res 2017;45:D712-22. [PMID: 27899636 DOI: 10.1093/nar/gkw1128] [Cited by in Crossref: 165] [Cited by in F6Publishing: 128] [Article Influence: 27.5] [Reference Citation Analysis]
24 Ehsani-Moghaddam B, Queenan JA, MacKenzie J, Birtwhistle RV. Mucopolysaccharidosis type II detection by Naïve Bayes Classifier: An example of patient classification for a rare disease using electronic medical records from the Canadian Primary Care Sentinel Surveillance Network. PLoS One 2018;13:e0209018. [PMID: 30566525 DOI: 10.1371/journal.pone.0209018] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 2.3] [Reference Citation Analysis]
25 Li Z, Huang Q, Chen X, Wang Y, Li J, Xie Y, Dai Z, Zou X. Identification of Drug-Disease Associations Using Information of Molecular Structures and Clinical Symptoms via Deep Convolutional Neural Network. Front Chem 2019;7:924. [PMID: 31998700 DOI: 10.3389/fchem.2019.00924] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 2.5] [Reference Citation Analysis]
26 Zhang Y, Zhang G. A Domain-Specific Terminology for Retinopathy of Prematurity and Its Applications in Clinical Settings. J Healthc Eng 2018;2018:9237319. [PMID: 29850007 DOI: 10.1155/2018/9237319] [Reference Citation Analysis]
27 Siu LL, Lawler M, Haussler D, Knoppers BM, Lewin J, Vis DJ, Liao RG, Andre F, Banks I, Barrett JC, Caldas C, Camargo AA, Fitzgerald RC, Mao M, Mattison JE, Pao W, Sellers WR, Sullivan P, Teh BT, Ward RL, ZenKlusen JC, Sawyers CL, Voest EE. Facilitating a culture of responsible and effective sharing of cancer genome data. Nat Med 2016;22:464-71. [PMID: 27149219 DOI: 10.1038/nm.4089] [Cited by in Crossref: 61] [Cited by in F6Publishing: 46] [Article Influence: 12.2] [Reference Citation Analysis]
28 Pope MK, Ratajska A, Johnsen H, Rypdal KB, Sejersted Y, Paus B. Diagnostics of Hereditary Connective Tissue Disorders by Genetic Next-Generation Sequencing. Genetic Testing and Molecular Biomarkers 2019;23:783-90. [DOI: 10.1089/gtmb.2019.0064] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
29 Su S, Zhang L, Liu J. An Effective Method to Measure Disease Similarity Using Gene and Phenotype Associations. Front Genet 2019;10:466. [PMID: 31164903 DOI: 10.3389/fgene.2019.00466] [Cited by in Crossref: 4] [Article Influence: 1.3] [Reference Citation Analysis]
30 Landrum MJ, Lee JM, Benson M, Brown G, Chao C, Chitipiralla S, Gu B, Hart J, Hoffman D, Hoover J, Jang W, Katz K, Ovetsky M, Riley G, Sethi A, Tully R, Villamarin-Salomon R, Rubinstein W, Maglott DR. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res 2016;44:D862-8. [PMID: 26582918 DOI: 10.1093/nar/gkv1222] [Cited by in Crossref: 1415] [Cited by in F6Publishing: 1182] [Article Influence: 202.1] [Reference Citation Analysis]
31 Alnazzawi N, Thompson P, Ananiadou S. Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource. PLoS One 2016;11:e0162287. [PMID: 27643689 DOI: 10.1371/journal.pone.0162287] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 1.5] [Reference Citation Analysis]
32 Kessler MD, Yerges-Armstrong L, Taub MA, Shetty AC, Maloney K, Jeng LJB, Ruczinski I, Levin AM, Williams LK, Beaty TH, Mathias RA, Barnes KC, O'Connor TD; Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA). Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry. Nat Commun 2016;7:12521. [PMID: 27725664 DOI: 10.1038/ncomms12521] [Cited by in Crossref: 45] [Cited by in F6Publishing: 31] [Article Influence: 7.5] [Reference Citation Analysis]
33 Latorre-Pellicer A, Ascaso Á, Trujillano L, Gil-Salvador M, Arnedo M, Lucia-Campos C, Antoñanzas-Pérez R, Marcos-Alcalde I, Parenti I, Bueno-Lozano G, Musio A, Puisac B, Kaiser FJ, Ramos FJ, Gómez-Puertas P, Pié J. Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes. Int J Mol Sci 2020;21:E1042. [PMID: 32033219 DOI: 10.3390/ijms21031042] [Cited by in Crossref: 10] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
34 De La Vega FM, Chowdhury S, Moore B, Frise E, McCarthy J, Hernandez EJ, Wong T, James K, Guidugli L, Agrawal PB, Genetti CA, Brownstein CA, Beggs AH, Löscher BS, Franke A, Boone B, Levy SE, Õunap K, Pajusalu S, Huentelman M, Ramsey K, Naymik M, Narayanan V, Veeraraghavan N, Billings P, Reese MG, Yandell M, Kingsmore SF. Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases. Genome Med 2021;13:153. [PMID: 34645491 DOI: 10.1186/s13073-021-00965-0] [Reference Citation Analysis]
35 de Bono B, Gillespie T, Surles-Zeigler MC, Kokash N, Grethe JS, Martone M. Representing Normal and Abnormal Physiology as Routes of Flow in ApiNATOMY. Front Physiol 2022;13:795303. [PMID: 35547570 DOI: 10.3389/fphys.2022.795303] [Reference Citation Analysis]
36 Köhler S. [From symptom to syndrome using modern software support]. Internist (Berl) 2018;59:766-75. [PMID: 29995249 DOI: 10.1007/s00108-018-0456-8] [Reference Citation Analysis]
37 Li P, Nie Y, Yu J. Fusing literature and full network data improves disease similarity computation. BMC Bioinformatics 2016;17:326. [PMID: 27578323 DOI: 10.1186/s12859-016-1205-4] [Cited by in Crossref: 11] [Cited by in F6Publishing: 4] [Article Influence: 1.8] [Reference Citation Analysis]
38 Song P, He J, Li F, Jin C. Innovative measures to combat rare diseases in China: The national rare diseases registry system, larger-scale clinical cohort studies, and studies in combination with precision medicine research. Intractable Rare Dis Res 2017;6:1-5. [PMID: 28357175 DOI: 10.5582/irdr.2017.01003] [Cited by in Crossref: 16] [Cited by in F6Publishing: 9] [Article Influence: 3.2] [Reference Citation Analysis]
39 Skene NG, Grant SG. Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment. Front Neurosci 2016;10:16. [PMID: 26858593 DOI: 10.3389/fnins.2016.00016] [Cited by in Crossref: 92] [Cited by in F6Publishing: 84] [Article Influence: 15.3] [Reference Citation Analysis]
40 Pazos F, Chagoyen M, Seoane P, A. G. Ranea J. CoMent: relationships between biomedical concepts inferred from the scientific literature. Journal of Molecular Biology 2022. [DOI: 10.1016/j.jmb.2022.167568] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
41 Worthey EA. Analysis and Annotation of Whole-Genome or Whole-Exome Sequencing Derived Variants for Clinical Diagnosis. Curr Protoc Hum Genet 2017;95:9.24.1-9.24.28. [PMID: 29044471 DOI: 10.1002/cphg.49] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 1.4] [Reference Citation Analysis]
42 Tammimies K. Genetic mechanisms of regression in autism spectrum disorder. Neuroscience & Biobehavioral Reviews 2019;102:208-20. [DOI: 10.1016/j.neubiorev.2019.04.022] [Cited by in Crossref: 12] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]
43 Soualmia LF, Charlet J. Efficient Results in Semantic Interoperability for Health Care. Findings from the Section on Knowledge Representation and Management. Yearb Med Inform 2016;:184-7. [PMID: 27830249 DOI: 10.15265/IY-2016-051] [Cited by in Crossref: 1] [Article Influence: 0.2] [Reference Citation Analysis]
44 Li MJ, Liu Z, Wang P, Wong MP, Nelson MR, Kocher JP, Yeager M, Sham PC, Chanock SJ, Xia Z, Wang J. GWASdb v2: an update database for human genetic variants identified by genome-wide association studies. Nucleic Acids Res 2016;44:D869-76. [PMID: 26615194 DOI: 10.1093/nar/gkv1317] [Cited by in Crossref: 110] [Cited by in F6Publishing: 97] [Article Influence: 15.7] [Reference Citation Analysis]
45 Godard P, Page M. PCAN: phenotype consensus analysis to support disease-gene association. BMC Bioinformatics 2016;17:518. [PMID: 27923364 DOI: 10.1186/s12859-016-1401-2] [Cited by in Crossref: 11] [Cited by in F6Publishing: 6] [Article Influence: 1.8] [Reference Citation Analysis]
46 Fakhro KA, Staudt MR, Ramstetter MD, Robay A, Malek JA, Badii R, Al-Marri AA, Abi Khalil C, Al-Shakaki A, Chidiac O, Stadler D, Zirie M, Jayyousi A, Salit J, Mezey JG, Crystal RG, Rodriguez-Flores JL. The Qatar genome: a population-specific tool for precision medicine in the Middle East. Hum Genome Var 2016;3:16016. [PMID: 27408750 DOI: 10.1038/hgv.2016.16] [Cited by in Crossref: 54] [Cited by in F6Publishing: 48] [Article Influence: 9.0] [Reference Citation Analysis]
47 Gusic M, Schottmann G, Feichtinger RG, Du C, Scholz C, Wagner M, Mayr JA, Lee CY, Yépez VA, Lorenz N, Morales-Gonzalez S, Panneman DM, Rötig A, Rodenburg RJT, Wortmann SB, Prokisch H, Schuelke M. Bi-Allelic UQCRFS1 Variants Are Associated with Mitochondrial Complex III Deficiency, Cardiomyopathy, and Alopecia Totalis. Am J Hum Genet 2020;106:102-11. [PMID: 31883641 DOI: 10.1016/j.ajhg.2019.12.005] [Cited by in Crossref: 21] [Cited by in F6Publishing: 18] [Article Influence: 10.5] [Reference Citation Analysis]
48 Brookes AJ, Robinson PN. Human genotype–phenotype databases: aims, challenges and opportunities. Nat Rev Genet 2015;16:702-15. [DOI: 10.1038/nrg3932] [Cited by in Crossref: 69] [Cited by in F6Publishing: 53] [Article Influence: 9.9] [Reference Citation Analysis]
49 Vos RA, Katayama T, Mishima H, Kawano S, Kawashima S, Kim JD, Moriya Y, Tokimatsu T, Yamaguchi A, Yamamoto Y, Wu H, Amstutz P, Antezana E, Aoki NP, Arakawa K, Bolleman JT, Bolton E, Bonnal RJP, Bono H, Burger K, Chiba H, Cohen KB, Deutsch EW, Fernández-Breis JT, Fu G, Fujisawa T, Fukushima A, García A, Goto N, Groza T, Hercus C, Hoehndorf R, Itaya K, Juty N, Kawashima T, Kim JH, Kinjo AR, Kotera M, Kozaki K, Kumagai S, Kushida T, Lütteke T, Matsubara M, Miyamoto J, Mohsen A, Mori H, Naito Y, Nakazato T, Nguyen-Xuan J, Nishida K, Nishida N, Nishide H, Ogishima S, Ohta T, Okuda S, Paten B, Perret JL, Prathipati P, Prins P, Queralt-Rosinach N, Shinmachi D, Suzuki S, Tabata T, Takatsuki T, Taylor K, Thompson M, Uchiyama I, Vieira B, Wei CH, Wilkinson M, Yamada I, Yamanaka R, Yoshitake K, Yoshizawa AC, Dumontier M, Kosaki K, Takagi T. BioHackathon 2015: Semantics of data for life sciences and reproducible research. F1000Res 2020;9:136. [PMID: 32308977 DOI: 10.12688/f1000research.18236.1] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
50 Garda S, Schwarz JM, Schuelke M, Leser U, Seelow D. Public data sources for regulatory genomic features. Medizinische Genetik 2021;33:167-77. [DOI: 10.1515/medgen-2021-2075] [Reference Citation Analysis]
51 Li Z, Liu Z, Jiang Y, Chen D, Ran X, Sun ZS, Wu J. mirVAFC: A Web Server for Prioritizations of Pathogenic Sequence Variants from Exome Sequencing Data via Classifications. Hum Mutat 2017;38:25-33. [PMID: 27676360 DOI: 10.1002/humu.23125] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.3] [Reference Citation Analysis]
52 Liu S, Crawford DC. Maturation and application of phenome-wide association studies. Trends Genet 2022:S0168-9525(21)00352-8. [PMID: 34991903 DOI: 10.1016/j.tig.2021.12.002] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
53 Falk MJ, Shen L, Gai X. From case studies to community knowledge base: MSeqDR provides a platform for the curation and genomic analysis of mitochondrial diseases. Cold Spring Harb Mol Case Stud 2016;2:a001065. [PMID: 27148591 DOI: 10.1101/mcs.a001065] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
54 Tebani A, Afonso C, Marret S, Bekri S. Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations. Int J Mol Sci 2016;17:E1555. [PMID: 27649151 DOI: 10.3390/ijms17091555] [Cited by in Crossref: 78] [Cited by in F6Publishing: 66] [Article Influence: 13.0] [Reference Citation Analysis]
55 McMurry JA, Köhler S, Washington NL, Balhoff JP, Borromeo C, Brush M, Carbon S, Conlin T, Dunn N, Engelstad M, Foster E, Gourdine JP, Jacobsen JO, Keith D, Laraway B, Xuan JN, Shefchek K, Vasilevsky NA, Yuan Z, Lewis SE, Hochheiser H, Groza T, Smedley D, Robinson PN, Mungall CJ, Haendel MA. Navigating the Phenotype Frontier: The Monarch Initiative. Genetics 2016;203:1491-5. [PMID: 27516611 DOI: 10.1534/genetics.116.188870] [Cited by in Crossref: 41] [Cited by in F6Publishing: 31] [Article Influence: 8.2] [Reference Citation Analysis]
56 Babić Božović I, Maver A, Leonardis L, Meznaric M, Osredkar D, Peterlin B. Diagnostic yield of exome sequencing in myopathies: Experience of a Slovenian tertiary centre. PLoS One 2021;16:e0252953. [PMID: 34106991 DOI: 10.1371/journal.pone.0252953] [Reference Citation Analysis]
57 Feng S, Liu S, Zhu C, Gong M, Zhu Y, Zhang S. National Rare Diseases Registry System of China and Related Cohort Studies: Vision and Roadmap. Hum Gene Ther 2018;29:128-35. [PMID: 29284292 DOI: 10.1089/hum.2017.215] [Cited by in Crossref: 12] [Cited by in F6Publishing: 11] [Article Influence: 4.0] [Reference Citation Analysis]
58 Schaefer J, Lehne M, Schepers J, Prasser F, Thun S. The use of machine learning in rare diseases: a scoping review. Orphanet J Rare Dis. 2020;15:145. [PMID: 32517778 DOI: 10.1186/s13023-020-01424-6] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 4.5] [Reference Citation Analysis]
59 Vissers LE, Veltman JA. Standardized phenotyping enhances Mendelian disease gene identification. Nat Genet 2015;47:1222-4. [PMID: 26506899 DOI: 10.1038/ng.3425] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 1.8] [Reference Citation Analysis]
60 Peng J, Hui W, Shang X. Measuring phenotype-phenotype similarity through the interactome. BMC Bioinformatics 2018;19:114. [PMID: 29671400 DOI: 10.1186/s12859-018-2102-9] [Cited by in Crossref: 22] [Cited by in F6Publishing: 17] [Article Influence: 5.5] [Reference Citation Analysis]
61 Han SK, Kim D, Lee H, Kim I, Kim S, Larracuente A. Divergence of Noncoding Regulatory Elements Explains Gene–Phenotype Differences between Human and Mouse Orthologous Genes. Molecular Biology and Evolution 2018;35:1653-67. [DOI: 10.1093/molbev/msy056] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
62 Thompson R, Papakonstantinou Ntalis A, Beltran S, Töpf A, de Paula Estephan E, Polavarapu K, 't Hoen PAC, Missier P, Lochmüller H. Increasing phenotypic annotation improves the diagnostic rate of exome sequencing in a rare neuromuscular disorder. Hum Mutat 2019;40:1797-812. [PMID: 31231902 DOI: 10.1002/humu.23792] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
63 Zhang W, Zhang H, Yang H, Li M, Xie Z, Li W. Computational resources associating diseases with genotypes, phenotypes and exposures. Brief Bioinform 2019;20:2098-115. [PMID: 30102366 DOI: 10.1093/bib/bby071] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 6.0] [Reference Citation Analysis]
64 Thessen AE, Walls RL, Vogt L, Singer J, Warren R, Buttigieg PL, Balhoff JP, Mungall CJ, McGuinness DL, Stucky BJ, Yoder MJ, Haendel MA. Transforming the study of organisms: Phenomic data models and knowledge bases. PLoS Comput Biol 2020;16:e1008376. [PMID: 33232313 DOI: 10.1371/journal.pcbi.1008376] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
65 Doğan T. HPO2GO: prediction of human phenotype ontology term associations for proteins using cross ontology annotation co-occurrences. PeerJ 2018;6:e5298. [PMID: 30083448 DOI: 10.7717/peerj.5298] [Cited by in Crossref: 10] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
66 Xue H, Peng J, Shang X. Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO. BMC Syst Biol 2019;13:34. [PMID: 30953559 DOI: 10.1186/s12918-019-0697-8] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
67 Newnham JP, Kemp MW, White SW, Arrese CA, Hart RJ, Keelan JA. Applying Precision Public Health to Prevent Preterm Birth. Front Public Health 2017;5:66. [PMID: 28421178 DOI: 10.3389/fpubh.2017.00066] [Cited by in Crossref: 20] [Cited by in F6Publishing: 18] [Article Influence: 4.0] [Reference Citation Analysis]
68 Wang Y, Zhang F, Byrd JB, Yu H, Ye X, He Y. Differential COVID-19 Symptoms Given Pandemic Locations, Time, and Comorbidities During the Early Pandemic. Front Med 2022;9:770031. [DOI: 10.3389/fmed.2022.770031] [Reference Citation Analysis]
69 Giannoula A, Centeno E, Mayer MA, Sanz F, Furlong LI. A system-level analysis of patient disease trajectories based on clinical, phenotypic and molecular similarities. Bioinformatics 2021;37:1435-43. [PMID: 33185649 DOI: 10.1093/bioinformatics/btaa964] [Reference Citation Analysis]
70 Fujiwara T, Yamamoto Y, Kim JD, Buske O, Takagi T. PubCaseFinder: A Case-Report-Based, Phenotype-Driven Differential-Diagnosis System for Rare Diseases. Am J Hum Genet 2018;103:389-99. [PMID: 30173820 DOI: 10.1016/j.ajhg.2018.08.003] [Cited by in Crossref: 19] [Cited by in F6Publishing: 12] [Article Influence: 4.8] [Reference Citation Analysis]
71 Baynam G, Bowman F, Lister K, Walker CE, Pachter N, Goldblatt J, Boycott KM, Gahl WA, Kosaki K, Adachi T, Ishii K, Mahede T, McKenzie F, Townshend S, Slee J, Kiraly-Borri C, Vasudevan A, Hawkins A, Broley S, Schofield L, Verhoef H, Groza T, Zankl A, Robinson PN, Haendel M, Brudno M, Mattick JS, Dinger ME, Roscioli T, Cowley MJ, Olry A, Hanauer M, Alkuraya FS, Taruscio D, Posada de la Paz M, Lochmüller H, Bushby K, Thompson R, Hedley V, Lasko P, Mina K, Beilby J, Tifft C, Davis M, Laing NG, Julkowska D, Le Cam Y, Terry SF, Kaufmann P, Eerola I, Norstedt I, Rath A, Suematsu M, Groft SC, Austin CP, Draghia-Akli R, Weeramanthri TS, Molster C, Dawkins HJS. Improved Diagnosis and Care for Rare Diseases through Implementation of Precision Public Health Framework. Adv Exp Med Biol 2017;1031:55-94. [PMID: 29214566 DOI: 10.1007/978-3-319-67144-4_4] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 2.0] [Reference Citation Analysis]
72 Wang Y, Li N, Su Z, Xu Y, Liu S, Chen Y, Li X, Shen Y, Hung C, Wang J, Wang X, Bodamer O. The phenotypic spectrum of Kabuki syndrome in patients of Chinese descent: A case series. Am J Med Genet A 2020;182:640-51. [PMID: 31883305 DOI: 10.1002/ajmg.a.61467] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 0.3] [Reference Citation Analysis]
73 Peng J, Xue H, Hui W, Lu J, Chen B, Jiang Q, Shang X, Wang Y. An online tool for measuring and visualizing phenotype similarities using HPO. BMC Genomics 2018;19:571. [PMID: 30367579 DOI: 10.1186/s12864-018-4927-z] [Cited by in Crossref: 3] [Article Influence: 0.8] [Reference Citation Analysis]
74 Takahashi Y, Mizusawa H. Initiative on Rare and Undiagnosed Disease in Japan. JMA J 2021;4:112-8. [PMID: 33997444 DOI: 10.31662/jmaj.2021-0003] [Reference Citation Analysis]
75 Chatr-Aryamontri A, Oughtred R, Boucher L, Rust J, Chang C, Kolas NK, O'Donnell L, Oster S, Theesfeld C, Sellam A, Stark C, Breitkreutz BJ, Dolinski K, Tyers M. The BioGRID interaction database: 2017 update. Nucleic Acids Res 2017;45:D369-79. [PMID: 27980099 DOI: 10.1093/nar/gkw1102] [Cited by in Crossref: 681] [Cited by in F6Publishing: 537] [Article Influence: 113.5] [Reference Citation Analysis]
76 Delavan B, Roberts R, Huang R, Bao W, Tong W, Liu Z. Computational drug repositioning for rare diseases in the era of precision medicine. Drug Discov Today 2018;23:382-94. [PMID: 29055182 DOI: 10.1016/j.drudis.2017.10.009] [Cited by in Crossref: 41] [Cited by in F6Publishing: 34] [Article Influence: 8.2] [Reference Citation Analysis]
77 O'Donnell-Luria AH, Miller DT. A Clinician's perspective on clinical exome sequencing. Hum Genet 2016;135:643-54. [PMID: 27126233 DOI: 10.1007/s00439-016-1662-x] [Cited by in Crossref: 26] [Cited by in F6Publishing: 21] [Article Influence: 4.3] [Reference Citation Analysis]
78 Rubinstein YR, Robinson PN, Gahl WA, Avillach P, Baynam G, Cederroth H, Goodwin RM, Groft SC, Hansson MG, Harris NL, Huser V, Mascalzoni D, McMurry JA, Might M, Nellaker C, Mons B, Paltoo DN, Pevsner J, Posada M, Rockett-Frase AP, Roos M, Rubinstein TB, Taruscio D, van Enckevort E, Haendel MA. The case for open science: rare diseases. JAMIA Open 2020;3:472-86. [PMID: 33426479 DOI: 10.1093/jamiaopen/ooaa030] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 3.5] [Reference Citation Analysis]
79 Pagano-Márquez R, Córdoba-Caballero J, Martínez-Poveda B, Quesada AR, Rojano E, Seoane P, Ranea JAG, Ángel Medina M. Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis. Brief Bioinform 2022:bbac220. [PMID: 35731990 DOI: 10.1093/bib/bbac220] [Reference Citation Analysis]
80 Kreimeyer K, Foster M, Pandey A, Arya N, Halford G, Jones SF, Forshee R, Walderhaug M, Botsis T. Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review. J Biomed Inform 2017;73:14-29. [PMID: 28729030 DOI: 10.1016/j.jbi.2017.07.012] [Cited by in Crossref: 156] [Cited by in F6Publishing: 116] [Article Influence: 31.2] [Reference Citation Analysis]
81 Schön U, Holzer A, Laner A, Kleinle S, Scharf F, Benet-Pagès A, Peschel O, Holinski-Feder E, Diebold I. HPO-driven virtual gene panel: a new efficient approach in molecular autopsy of sudden unexplained death. BMC Med Genomics 2021;14:94. [PMID: 33789662 DOI: 10.1186/s12920-021-00946-7] [Reference Citation Analysis]
82 Wu J, Yu X, Gao W. Disequilibrium multi-dividing ontology learning algorithm. Communications in Statistics - Theory and Methods 2017;46:8925-42. [DOI: 10.1080/03610926.2016.1197254] [Cited by in Crossref: 8] [Cited by in F6Publishing: 1] [Article Influence: 1.6] [Reference Citation Analysis]
83 Tan PP, Rogic S, Zoubarev A, McDonald C, Lui F, Charathsandran G, Jacobson M, Belmadani M, Leong J, Van Rossum T, Portales-Casamar E, Qiao Y, Calli K, Liu X, Hudson M, Rajcan-Separovic E, Lewis MS, Pavlidis P. Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb. Hum Mutat 2016;37:719-26. [PMID: 27158917 DOI: 10.1002/humu.23011] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.3] [Reference Citation Analysis]
84 Arnal IR, Andrade JR, Hally MM, Baviera LCB, Tirado DG, Martín SHC, de la Calle Navarro E, Álvarez AMV. Diagnostic action against hypertransaminasemia in paediatrics: Consensus document of Sociedad Española de Gastroenterología, Hepatología y Nutrición Pediátrica (SEGHNP), Asociación Española de Pediatría de Atención Primaria (AEPap) and Sociedad Española de Pediatría de Atención Primaria (SEPEAP). Anales de Pediatría (English Edition) 2022. [DOI: 10.1016/j.anpede.2022.04.009] [Reference Citation Analysis]
85 Guo F, Tang X, Zhang W, Wei J, Tang S, Wu H, Yang H. Exploration of the mechanism of traditional Chinese medicine by AI approach using unsupervised machine learning for cellular functional similarity of compounds in heterogeneous networks, XiaoErFuPi granules as an example. Pharmacological Research 2020;160:105077. [DOI: 10.1016/j.phrs.2020.105077] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 2.5] [Reference Citation Analysis]
86 Takahashi Y, Date H, Oi H, Adachi T, Imanishi N, Kimura E, Takizawa H, Kosugi S, Matsumoto N, Kosaki K, Matsubara Y, Mizusawa H; IRUD Consortium. Six years' accomplishment of the Initiative on Rare and Undiagnosed Diseases: nationwide project in Japan to discover causes, mechanisms, and cures. J Hum Genet 2022. [PMID: 35318459 DOI: 10.1038/s10038-022-01025-0] [Reference Citation Analysis]
87 Logotheti M, Pilalis E, Venizelos N, Kolisis F, Chatziioannou A; 1 Neuropsychiatric Research Laboratory, Faculty of Medicine and Health, School of Health and Medical Sciences, Örebro University, Örebro, Sweden. . AIMS Bioengineering 2016;3:552-65. [DOI: 10.3934/bioeng.2016.4.552] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis]
88 Tcheandjieu C, Aguirre M, Gustafsson S, Saha P, Potiny P, Haendel M, Ingelsson E, Rivas MA, Priest JR. A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population. PLoS Genet 2020;16:e1008802. [PMID: 33226994 DOI: 10.1371/journal.pgen.1008802] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
89 Salnikova LE, Chernyshova EV, Anastasevich LA, Larin SS. Gene- and Disease-Based Expansion of the Knowledge on Inborn Errors of Immunity. Front Immunol 2019;10:2475. [PMID: 31695696 DOI: 10.3389/fimmu.2019.02475] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
90 Baker E, Bubier JA, Reynolds T, Langston MA, Chesler EJ. GeneWeaver: data driven alignment of cross-species genomics in biology and disease. Nucleic Acids Res 2016;44:D555-9. [PMID: 26656951 DOI: 10.1093/nar/gkv1329] [Cited by in Crossref: 20] [Cited by in F6Publishing: 14] [Article Influence: 2.9] [Reference Citation Analysis]
91 Mishima H, Suzuki H, Doi M, Miyazaki M, Watanabe S, Matsumoto T, Morifuji K, Moriuchi H, Yoshiura KI, Kondoh T, Kosaki K. Evaluation of Face2Gene using facial images of patients with congenital dysmorphic syndromes recruited in Japan. J Hum Genet 2019;64:789-94. [PMID: 31138847 DOI: 10.1038/s10038-019-0619-z] [Cited by in Crossref: 24] [Cited by in F6Publishing: 18] [Article Influence: 8.0] [Reference Citation Analysis]
92 Maiella S, Olry A, Hanauer M, Lanneau V, Lourghi H, Donadille B, Rodwell C, Köhler S, Seelow D, Jupp S, Parkinson H, Groza T, Brudno M, Robinson PN, Rath A. Harmonising phenomics information for a better interoperability in the rare disease field. Eur J Med Genet 2018;61:706-14. [PMID: 29425702 DOI: 10.1016/j.ejmg.2018.01.013] [Cited by in Crossref: 13] [Cited by in F6Publishing: 12] [Article Influence: 3.3] [Reference Citation Analysis]
93 Lelieveld SH, Veltman JA, Gilissen C. Novel bioinformatic developments for exome sequencing. Hum Genet 2016;135:603-14. [PMID: 27075447 DOI: 10.1007/s00439-016-1658-6] [Cited by in Crossref: 27] [Cited by in F6Publishing: 20] [Article Influence: 4.5] [Reference Citation Analysis]
94 Sealfon RSG, Mariani LH, Kretzler M, Troyanskaya OG. Machine learning, the kidney, and genotype-phenotype analysis. Kidney Int 2020;97:1141-9. [PMID: 32359808 DOI: 10.1016/j.kint.2020.02.028] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 4.5] [Reference Citation Analysis]
95 Krude H, Mundlos S, Øien NC, Opitz R, Schuelke M. What can go wrong in the non-coding genome and how to interpret whole genome sequencing data. Medizinische Genetik 2021;33:121-31. [DOI: 10.1515/medgen-2021-2071] [Reference Citation Analysis]
96 Lelieveld SH, Veltman JA, Gilissen C. Novel bioinformatic developments for exome sequencing. Hum Genet 2016;135:603-14. [PMID: 27075447 DOI: 10.1007/s00439-016-1658-6] [Cited by in Crossref: 29] [Cited by in F6Publishing: 1] [Article Influence: 4.8] [Reference Citation Analysis]
97 Liu Z, Fang H, Slikker W, Tong W. Potential Reuse of Oncology Drugs in the Treatment of Rare Diseases. Trends in Pharmacological Sciences 2016;37:843-57. [DOI: 10.1016/j.tips.2016.06.010] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 1.5] [Reference Citation Analysis]
98 Jia J, An Z, Ming Y, Guo Y, Li W, Liang Y, Guo D, Li X, Tai J, Chen G, Jin Y, Liu Z, Ni X, Shi T. eRAM: encyclopedia of rare disease annotations for precision medicine. Nucleic Acids Res 2018;46:D937-43. [PMID: 29106618 DOI: 10.1093/nar/gkx1062] [Cited by in Crossref: 20] [Cited by in F6Publishing: 17] [Article Influence: 6.7] [Reference Citation Analysis]
99 Sarntivijai S, Vasant D, Jupp S, Saunders G, Bento AP, Gonzalez D, Betts J, Hasan S, Koscielny G, Dunham I, Parkinson H, Malone J. Linking rare and common disease: mapping clinical disease-phenotypes to ontologies in therapeutic target validation. J Biomed Semantics. 2016;7:8. [PMID: 27011785 DOI: 10.1186/s13326-016-0051-7] [Cited by in Crossref: 26] [Cited by in F6Publishing: 23] [Article Influence: 4.3] [Reference Citation Analysis]
100 Trinh J, Kandaswamy KK, Werber M, Weiss MER, Oprea G, Kishore S, Lohmann K, Rolfs A. Novel pathogenic variants and multiple molecular diagnoses in neurodevelopmental disorders. J Neurodev Disord 2019;11:11. [PMID: 31238879 DOI: 10.1186/s11689-019-9270-4] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 3.7] [Reference Citation Analysis]
101 Callahan A, Abeyruwan SW, Al-Ali H, Sakurai K, Ferguson AR, Popovich PG, Shah NH, Visser U, Bixby JL, Lemmon VP. RegenBase: a knowledge base of spinal cord injury biology for translational research. Database (Oxford) 2016;2016:baw040. [PMID: 27055827 DOI: 10.1093/database/baw040] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 0.8] [Reference Citation Analysis]
102 Gao W, Zhu L, Guo Y, Wang K, Guirao JL, Gao W. Ontology learning algorithm for similarity measuring and ontology mapping using linear programming. IFS 2017;33:3153-63. [DOI: 10.3233/jifs-169367] [Cited by in Crossref: 51] [Article Influence: 10.2] [Reference Citation Analysis]
103 Thompson P, Ananiadou S. HYPHEN: A flexible, hybrid method to map phenotype concept mentions to terminological resources. TERM 2018;24:91-121. [DOI: 10.1075/term.00015.tho] [Cited by in Crossref: 3] [Article Influence: 0.8] [Reference Citation Analysis]
104 Sarntivijai S, Zhang S, Jagannathan DG, Zaman S, Burkhart KK, Omenn GS, He Y, Athey BD, Abernethy DR. Linking MedDRA(®)-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors. Drug Saf 2016;39:697-707. [PMID: 27003817 DOI: 10.1007/s40264-016-0414-0] [Cited by in Crossref: 15] [Cited by in F6Publishing: 15] [Article Influence: 3.0] [Reference Citation Analysis]
105 Dhombres F, Bodenreider O. Interoperability between phenotypes in research and healthcare terminologies--Investigating partial mappings between HPO and SNOMED CT. J Biomed Semantics 2016;7:3. [PMID: 26865946 DOI: 10.1186/s13326-016-0047-3] [Cited by in Crossref: 24] [Cited by in F6Publishing: 19] [Article Influence: 4.0] [Reference Citation Analysis]
106 Köhler S, Robinson PN. [Diagnostics in human genetics : Integration of phenotypic and genomic data]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2017;60:542-9. [PMID: 28293716 DOI: 10.1007/s00103-017-2538-5] [Reference Citation Analysis]
107 Köhler S, Øien NC, Buske OJ, Groza T, Jacobsen JOB, McNamara C, Vasilevsky N, Carmody LC, Gourdine JP, Gargano M, McMurry JA, Danis D, Mungall CJ, Smedley D, Haendel M, Robinson PN. Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics. Curr Protoc Hum Genet 2019;103:e92. [PMID: 31479590 DOI: 10.1002/cphg.92] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 2.0] [Reference Citation Analysis]
108 Jia J, Shi T. Towards efficiency in rare disease research: what is distinctive and important? Sci China Life Sci 2017;60:686-91. [PMID: 28639105 DOI: 10.1007/s11427-017-9099-3] [Cited by in Crossref: 18] [Cited by in F6Publishing: 15] [Article Influence: 3.6] [Reference Citation Analysis]
109 Prieto-González D, Castilla-Rodríguez I, González E, Couce ML. Towards the automated economic assessment of newborn screening for rare diseases. J Biomed Inform 2019;95:103216. [PMID: 31128259 DOI: 10.1016/j.jbi.2019.103216] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
110 Oughtred R, Stark C, Breitkreutz BJ, Rust J, Boucher L, Chang C, Kolas N, O'Donnell L, Leung G, McAdam R, Zhang F, Dolma S, Willems A, Coulombe-Huntington J, Chatr-Aryamontri A, Dolinski K, Tyers M. The BioGRID interaction database: 2019 update. Nucleic Acids Res 2019;47:D529-41. [PMID: 30476227 DOI: 10.1093/nar/gky1079] [Cited by in Crossref: 536] [Cited by in F6Publishing: 433] [Article Influence: 268.0] [Reference Citation Analysis]
111 Dulovic-Mahlow M, Trinh J, Kandaswamy KK, Braathen GJ, Di Donato N, Rahikkala E, Beblo S, Werber M, Krajka V, Busk ØL, Baumann H, Al-Sannaa NA, Hinrichs F, Affan R, Navot N, Al Balwi MA, Oprea G, Holla ØL, Weiss MER, Jamra RA, Kahlert AK, Kishore S, Tveten K, Vos M, Rolfs A, Lohmann K. De Novo Variants in TAOK1 Cause Neurodevelopmental Disorders. Am J Hum Genet 2019;105:213-20. [PMID: 31230721 DOI: 10.1016/j.ajhg.2019.05.005] [Cited by in Crossref: 15] [Cited by in F6Publishing: 14] [Article Influence: 5.0] [Reference Citation Analysis]
112 Peng J, Bai K, Shang X, Wang G, Xue H, Jin S, Cheng L, Wang Y, Chen J. Predicting disease-related genes using integrated biomedical networks. BMC Genomics 2017;18:1043. [PMID: 28198675 DOI: 10.1186/s12864-016-3263-4] [Cited by in Crossref: 27] [Cited by in F6Publishing: 21] [Article Influence: 5.4] [Reference Citation Analysis]
113 Schulze KV, Swaminathan S, Howell S, Jajoo A, Lie NC, Brown O, Sadat R, Hall N, Zhao L, Marshall K, May T, Reid ME, Taylor-Bryan C, Wang X, Belmont JW, Guan Y, Manary MJ, Trehan I, McKenzie CA, Hanchard NA. Edematous severe acute malnutrition is characterized by hypomethylation of DNA. Nat Commun 2019;10:5791. [PMID: 31857576 DOI: 10.1038/s41467-019-13433-6] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 3.7] [Reference Citation Analysis]
114 Piñero J, Bravo À, Queralt-Rosinach N, Gutiérrez-Sacristán A, Deu-Pons J, Centeno E, García-García J, Sanz F, Furlong LI. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res 2017;45:D833-9. [PMID: 27924018 DOI: 10.1093/nar/gkw943] [Cited by in Crossref: 859] [Cited by in F6Publishing: 731] [Article Influence: 143.2] [Reference Citation Analysis]
115 Chong JX, Yu JH, Lorentzen P, Park KM, Jamal SM, Tabor HK, Rauch A, Saenz MS, Boltshauser E, Patterson KE, Nickerson DA, Bamshad MJ. Gene discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features. Genet Med 2016;18:788-95. [PMID: 26656649 DOI: 10.1038/gim.2015.161] [Cited by in Crossref: 52] [Cited by in F6Publishing: 46] [Article Influence: 7.4] [Reference Citation Analysis]
116 Bastarache L, Hughey JJ, Hebbring S, Marlo J, Zhao W, Ho WT, Van Driest SL, McGregor TL, Mosley JD, Wells QS, Temple M, Ramirez AH, Carroll R, Osterman T, Edwards T, Ruderfer D, Velez Edwards DR, Hamid R, Cogan J, Glazer A, Wei WQ, Feng Q, Brilliant M, Zhao ZJ, Cox NJ, Roden DM, Denny JC. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 2018;359:1233-9. [PMID: 29590070 DOI: 10.1126/science.aal4043] [Cited by in Crossref: 104] [Cited by in F6Publishing: 66] [Article Influence: 26.0] [Reference Citation Analysis]
117 Deisseroth CA, Birgmeier J, Bodle EE, Kohler JN, Matalon DR, Nazarenko Y, Genetti CA, Brownstein CA, Schmitz-Abe K, Schoch K, Cope H, Signer R, Martinez-Agosto JA, Shashi V, Beggs AH, Wheeler MT, Bernstein JA, Bejerano G; Undiagnosed Diseases Network. ClinPhen extracts and prioritizes patient phenotypes directly from medical records to expedite genetic disease diagnosis. Genet Med 2019;21:1585-93. [PMID: 30514889 DOI: 10.1038/s41436-018-0381-1] [Cited by in Crossref: 28] [Cited by in F6Publishing: 21] [Article Influence: 7.0] [Reference Citation Analysis]
118 Hill DP, Harper A, Malcolm J, McAndrews MS, Mockus SM, Patterson SE, Reynolds T, Baker EJ, Bult CJ, Chesler EJ, Blake JA. Cisplatin-resistant triple-negative breast cancer subtypes: multiple mechanisms of resistance. BMC Cancer. 2019;19:1039. [PMID: 31684899 DOI: 10.1186/s12885-019-6278-9] [Cited by in Crossref: 19] [Cited by in F6Publishing: 17] [Article Influence: 6.3] [Reference Citation Analysis]
119 Pearson NM, Stolte C, Shi K, Beren F, Abul-Husn NS, Bertier G, Brown K, Diaz GA, Odgis JA, Suckiel SA, Horowitz CR, Wasserstein M, Gelb BD, Kenny EE, Gagnon C, Jobanputra V, Bloom T, Greally JM. GenomeDiver: a platform for phenotype-guided medical genomic diagnosis. Genet Med 2021. [PMID: 34113009 DOI: 10.1038/s41436-021-01219-5] [Reference Citation Analysis]
120 Poux S, Gaudet P. Best Practices in Manual Annotation with the Gene Ontology. Methods Mol Biol 2017;1446:41-54. [PMID: 27812934 DOI: 10.1007/978-1-4939-3743-1_4] [Cited by in Crossref: 16] [Cited by in F6Publishing: 11] [Article Influence: 3.2] [Reference Citation Analysis]