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For: Saini N, Bakshi S, Sharma S. In-silico approach for drug induced liver injury prediction: Recent advances. Toxicol Lett 2018;295:288-95. [PMID: 29981923 DOI: 10.1016/j.toxlet.2018.06.1216] [Cited by in Crossref: 13] [Cited by in F6Publishing: 10] [Article Influence: 4.3] [Reference Citation Analysis]
Number Citing Articles
1 Adeluwa T, McGregor BA, Guo K, Hur J. Predicting Drug-Induced Liver Injury Using Machine Learning on a Diverse Set of Predictors. Front Pharmacol 2021;12:648805. [PMID: 34483896 DOI: 10.3389/fphar.2021.648805] [Reference Citation Analysis]
2 Chierici M, Francescatto M, Bussola N, Jurman G, Furlanello C. Predictability of drug-induced liver injury by machine learning. Biol Direct 2020;15:3. [PMID: 32054490 DOI: 10.1186/s13062-020-0259-4] [Cited by in Crossref: 20] [Cited by in F6Publishing: 15] [Article Influence: 20.0] [Reference Citation Analysis]
3 Coffin AB, Boney R, Hill J, Tian C, Steyger PS. Detecting Novel Ototoxins and Potentiation of Ototoxicity by Disease Settings. Front Neurol 2021;12:725566. [PMID: 34489859 DOI: 10.3389/fneur.2021.725566] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 He S, Zhang C, Zhou P, Zhang X, Ye T, Wang R, Sun G, Sun X. Herb-Induced Liver Injury: Phylogenetic Relationship, Structure-Toxicity Relationship, and Herb-Ingredient Network Analysis. Int J Mol Sci 2019;20:E3633. [PMID: 31349548 DOI: 10.3390/ijms20153633] [Cited by in Crossref: 16] [Cited by in F6Publishing: 15] [Article Influence: 8.0] [Reference Citation Analysis]
5 Jaganathan K, Tayara H, Chong KT. Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets. Int J Mol Sci 2021;22:8073. [PMID: 34360838 DOI: 10.3390/ijms22158073] [Reference Citation Analysis]
6 Garzel B, Zhang L, Huang SM, Wang H. A Change in Bile Flow: Looking Beyond Transporter Inhibition in the Development of Drug-induced Cholestasis. Curr Drug Metab 2019;20:621-32. [PMID: 31288715 DOI: 10.2174/1389200220666190709170256] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 8.0] [Reference Citation Analysis]
7 Wang J, Bwayi M, Gee RRF, Chen T. PXR-mediated idiosyncratic drug-induced liver injury: mechanistic insights and targeting approaches. Expert Opin Drug Metab Toxicol 2020;16:711-22. [PMID: 32500752 DOI: 10.1080/17425255.2020.1779701] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Roy H, Nandi S. In-Silico Modeling in Drug Metabolism and Interaction: Current Strategies of Lead Discovery. Curr Pharm Des 2019;25:3292-305. [PMID: 31481001 DOI: 10.2174/1381612825666190903155935] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
9 Singh N, Chaput L, Villoutreix BO. Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace. Brief Bioinform 2021;22:1790-818. [PMID: 32187356 DOI: 10.1093/bib/bbaa034] [Cited by in Crossref: 18] [Cited by in F6Publishing: 17] [Article Influence: 18.0] [Reference Citation Analysis]
10 Zhuo Y, Zhang Y, Li M, Wu H, Gong S, Hu X, Fu Y, Shen X, Sun B, Wu JL, Li N. Hepatotoxic evaluation of toosendanin via biomarker quantification and pathway mapping of large-scale chemical proteomics. Food Chem Toxicol 2021;153:112257. [PMID: 34000341 DOI: 10.1016/j.fct.2021.112257] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]