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For: Kong W, Tu X, Huang W, Yang Y, Xie Z, Huang Z. Prediction and Optimization of Na V 1.7 Sodium Channel Inhibitors Based on Machine Learning and Simulated Annealing. J Chem Inf Model 2020;60:2739-53. [DOI: 10.1021/acs.jcim.9b01180] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Liu W, Hopkins AM, Yan P, Du S, Luyt LG, Li Y, Hou J. Can machine learning ‘transform’ peptides/peptidomimetics into small molecules? A case study with ghrelin receptor ligands. Mol Divers 2022. [DOI: 10.1007/s11030-022-10555-w] [Reference Citation Analysis]
2 Gu Y, Zheng S, Yin Q, Jiang R, Li J. REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction. Computers in Biology and Medicine 2022;150:106127. [DOI: 10.1016/j.compbiomed.2022.106127] [Reference Citation Analysis]
3 Zhu Z, Deng Z, Wang Q, Wang Y, Zhang D, Xu R, Guo L, Wen H. Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design. Front Pharmacol 2022;13:939555. [DOI: 10.3389/fphar.2022.939555] [Reference Citation Analysis]
4 Gu Y, Zheng S, Xu Z, Yin Q, Li L, Li J. An efficient curriculum learning-based strategy for molecular graph learning. Briefings in Bioinformatics. [DOI: 10.1093/bib/bbac099] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Zhu J, Wang J, Wang X, Gao M, Guo B, Gao M, Liu J, Yu Y, Wang L, Kong W, An Y, Liu Z, Sun X, Huang Z, Zhou H, Zhang N, Zheng R, Xie Z. Prediction of drug efficacy from transcriptional profiles with deep learning. Nat Biotechnol 2021. [PMID: 34140681 DOI: 10.1038/s41587-021-00946-z] [Cited by in Crossref: 14] [Cited by in F6Publishing: 16] [Article Influence: 14.0] [Reference Citation Analysis]
6 Kawai K, Tomonou M, Machida Y, Karuo Y, Tarui A, Sato K, Ikeda Y, Kinashi T, Omote M. Effect of Learning Dataset for Identification of Active Molecules: A Case Study of Integrin αIIbβ3 Inhibitors. Mol Inform 2021;40:e2060040. [PMID: 33738924 DOI: 10.1002/minf.202060040] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
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8 Vatansever S, Schlessinger A, Wacker D, Kaniskan HÜ, Jin J, Zhou MM, Zhang B. Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions. Med Res Rev 2021;41:1427-73. [PMID: 33295676 DOI: 10.1002/med.21764] [Cited by in Crossref: 32] [Cited by in F6Publishing: 37] [Article Influence: 16.0] [Reference Citation Analysis]
9 Kong W, Wang W, An J. Prediction of 5-hydroxytryptamine transporter inhibitors based on machine learning. Comput Biol Chem 2020;87:107303. [PMID: 32563857 DOI: 10.1016/j.compbiolchem.2020.107303] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]