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For: Chandrasekaran SN, Ceulemans H, Boyd JD, Carpenter AE. Image-based profiling for drug discovery: due for a machine-learning upgrade? Nat Rev Drug Discov 2021;20:145-59. [PMID: 33353986 DOI: 10.1038/s41573-020-00117-w] [Cited by in Crossref: 11] [Cited by in F6Publishing: 13] [Article Influence: 5.5] [Reference Citation Analysis]
Number Citing Articles
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3 de Almeida A, Parthimos D, Dew H, Smart O, Wiltshire M, Errington RJ. Aquaglyceroporin-3's Expression and Cellular Localization Is Differentially Modulated by Hypoxia in Prostate Cancer Cell Lines. Cells 2021;10:838. [PMID: 33917751 DOI: 10.3390/cells10040838] [Reference Citation Analysis]
4 Trapotsi M, Hosseini-gerami L, Bender A. Computational analyses of mechanism of action (MoA): data, methods and integration. RSC Chem Biol . [DOI: 10.1039/d1cb00069a] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Foster B, Attwood M, Gibbs-Seymour I. Tools for Decoding Ubiquitin Signaling in DNA Repair. Front Cell Dev Biol 2021;9:760226. [PMID: 34950659 DOI: 10.3389/fcell.2021.760226] [Reference Citation Analysis]
6 Zaritsky A, Jamieson AR, Welf ES, Nevarez A, Cillay J, Eskiocak U, Cantarel BL, Danuser G. Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma. Cell Syst 2021;12:733-747.e6. [PMID: 34077708 DOI: 10.1016/j.cels.2021.05.003] [Reference Citation Analysis]
7 Zamanian M, Chan JD. High-content approaches to anthelmintic drug screening. Trends Parasitol 2021;37:780-9. [PMID: 34092518 DOI: 10.1016/j.pt.2021.05.004] [Reference Citation Analysis]
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9 Driscoll MK, Zaritsky A. Data science in cell imaging. J Cell Sci 2021;134:jcs254292. [PMID: 33795377 DOI: 10.1242/jcs.254292] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
10 Hollandi R, Moshkov N, Paavolainen L, Tasnadi E, Piccinini F, Horvath P. Nucleus segmentation: towards automated solutions. Trends in Cell Biology 2022. [DOI: 10.1016/j.tcb.2021.12.004] [Reference Citation Analysis]
11 Ji Y, Lotfollahi M, Wolf FA, Theis FJ. Machine learning for perturbational single-cell omics. Cell Syst 2021;12:522-37. [PMID: 34139164 DOI: 10.1016/j.cels.2021.05.016] [Reference Citation Analysis]
12 Cova T, Vitorino C, Ferreira M, Nunes S, Rondon-Villarreal P, Pais A. Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors. Methods Mol Biol 2022;2390:321-47. [PMID: 34731476 DOI: 10.1007/978-1-0716-1787-8_14] [Reference Citation Analysis]
13 Dafniet B, Cerisier N, Boezio B, Clary A, Ducrot P, Dorval T, Gohier A, Brown D, Audouze K, Taboureau O. Development of a chemogenomics library for phenotypic screening. J Cheminform 2021;13:91. [PMID: 34819133 DOI: 10.1186/s13321-021-00569-1] [Reference Citation Analysis]
14 Mak KK, Balijepalli MK, Pichika MR. Success stories of AI in drug discovery - where do things stand? Expert Opin Drug Discov 2021;:1-14. [PMID: 34553659 DOI: 10.1080/17460441.2022.1985108] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
15 Renner H, Schöler HR, Bruder JM. Combining Automated Organoid Workflows With Artificial Intelligence-Based Analyses: Opportunities to Build a New Generation of Interdisciplinary High-Throughput Screens for Parkinson's Disease and Beyond. Mov Disord 2021. [PMID: 34498298 DOI: 10.1002/mds.28775] [Reference Citation Analysis]
16 Ashraf M, Khalilitousi M, Laksman Z. Applying Machine Learning to Stem Cell Culture and Differentiation. Curr Protoc 2021;1:e261. [PMID: 34529356 DOI: 10.1002/cpz1.261] [Reference Citation Analysis]
17 Kudo T, Lane K, Covert MW. A multiplexed epitope barcoding strategy that enables dynamic cellular phenotypic screens. Cell Syst 2022:S2405-4712(22)00084-9. [PMID: 35316656 DOI: 10.1016/j.cels.2022.02.006] [Reference Citation Analysis]
18 McCoubrey LE, Elbadawi M, Orlu M, Gaisford S, Basit AW. Harnessing machine learning for development of microbiome therapeutics. Gut Microbes 2021;13:1-20. [PMID: 33522391 DOI: 10.1080/19490976.2021.1872323] [Cited by in Crossref: 11] [Cited by in F6Publishing: 9] [Article Influence: 11.0] [Reference Citation Analysis]
19 Rigamonti A, Feuerhake F, Donadon M, Locati M, Marchesi F. Histopathological and Immune Prognostic Factors in Colo-Rectal Liver Metastases. Cancers (Basel) 2021;13:1075. [PMID: 33802446 DOI: 10.3390/cancers13051075] [Reference Citation Analysis]
20 Vickers A, Tewary M, Laddach A, Poletti M, Salameti V, Fraternali F, Danovi D, Watt FM. Plating human iPSC lines on micropatterned substrates reveals role for ITGB1 nsSNV in endoderm formation. Stem Cell Reports 2021;16:2628-41. [PMID: 34678211 DOI: 10.1016/j.stemcr.2021.09.017] [Reference Citation Analysis]
21 Cho NH, Cheveralls KC, Brunner AD, Kim K, Michaelis AC, Raghavan P, Kobayashi H, Savy L, Li JY, Canaj H, Kim JYS, Stewart EM, Gnann C, McCarthy F, Cabrera JP, Brunetti RM, Chhun BB, Dingle G, Hein MY, Huang B, Mehta SB, Weissman JS, Gómez-Sjöberg R, Itzhak DN, Royer LA, Mann M, Leonetti MD. OpenCell: Endogenous tagging for the cartography of human cellular organization. Science 2022;375:eabi6983. [PMID: 35271311 DOI: 10.1126/science.abi6983] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
22 Giri AK, Ianevski A. High-throughput screening for drug discovery targeting the cancer cell-microenvironment interactions in hematological cancers. Expert Opin Drug Discov 2021;:1-10. [PMID: 34743621 DOI: 10.1080/17460441.2022.1991306] [Reference Citation Analysis]
23 Vulliard L, Hancock J, Kamnev A, Fell CW, Ferreira da Silva J, Loizou JI, Nagy V, Dupré L, Menche J. BioProfiling.jl: Profiling biological perturbations with high-content imaging in single cells and heterogeneous populations. Bioinformatics 2021:btab853. [PMID: 34935929 DOI: 10.1093/bioinformatics/btab853] [Reference Citation Analysis]