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Cited by in F6Publishing
For: Mora JR, Marrero-Ponce Y, García-Jacas CR, Suarez Causado A. Ensemble Models Based on QuBiLS-MAS Features and Shallow Learning for the Prediction of Drug-Induced Liver Toxicity: Improving Deep Learning and Traditional Approaches. Chem Res Toxicol 2020;33:1855-73. [PMID: 32406679 DOI: 10.1021/acs.chemrestox.0c00030] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Feng H, Zhang L, Li S, Liu L, Yang T, Yang P, Zhao J, Arkin IT, Liu H. Predicting the reproductive toxicity of chemicals using ensemble learning methods and molecular fingerprints. Toxicol Lett 2021;340:4-14. [PMID: 33421549 DOI: 10.1016/j.toxlet.2021.01.002] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 4.0] [Reference Citation Analysis]
2 Cuesta SA, Mora JR, Márquez EA. In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2. Molecules 2021;26:1100. [PMID: 33669720 DOI: 10.3390/molecules26041100] [Reference Citation Analysis]
3 Ma H, An W, Wang Y, Sun H, Huang R, Huang J. Deep Graph Learning with Property Augmentation for Predicting Drug-Induced Liver Injury. Chem Res Toxicol 2021;34:495-506. [PMID: 33347312 DOI: 10.1021/acs.chemrestox.0c00322] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
4 Wang Y, Chen X, Zalesny R. Joint Decision-Making Model Based on Consensus Modeling Technology for the Prediction of Drug-Induced Liver Injury. Journal of Chemistry 2021;2021:1-20. [DOI: 10.1155/2021/2293871] [Reference Citation Analysis]
5 Cabrera N, Mora JR, Márquez E, Flores-Morales V, Calle L, Cortés E. QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds. SAR QSAR Environ Res 2021;32:29-50. [PMID: 33241943 DOI: 10.1080/1062936X.2020.1848914] [Reference Citation Analysis]
6 Ivanov SM, Lagunin AA, Filimonov DA, Poroikov VV. Relationships between the Structure and Severe Drug-Induced Liver Injury for Low, Medium, and High Doses of Drugs. Chem Res Toxicol 2022. [PMID: 35172101 DOI: 10.1021/acs.chemrestox.1c00307] [Reference Citation Analysis]
7 Fernandes PO, Martins DM, de Souza Bozzi A, Martins JPA, de Moraes AH, Maltarollo VG. Molecular insights on ABL kinase activation using tree-based machine learning models and molecular docking. Mol Divers 2021;25:1301-14. [PMID: 34191245 DOI: 10.1007/s11030-021-10261-z] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Calle L, Marrero-ponce Y, Mora JR. Molecular simulation of the (GPx)-like antioxidant activity of ebselen derivatives through machine learning techniques. Molecular Simulation 2021;47:1402-10. [DOI: 10.1080/08927022.2021.1975039] [Reference Citation Analysis]
9 Venkatraman V. FP-ADMET: a compendium of fingerprint-based ADMET prediction models. J Cheminform 2021;13:75. [PMID: 34583740 DOI: 10.1186/s13321-021-00557-5] [Reference Citation Analysis]
10 Li T, Tong W, Roberts R, Liu Z, Thakkar S. DeepDILI: Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation. Chem Res Toxicol 2021;34:550-65. [PMID: 33356151 DOI: 10.1021/acs.chemrestox.0c00374] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
11 Cabrera N, Cuesta SA, Mora JR, Calle L, Márquez EA, Kaunas R, Paz JL. In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study. Pharmaceutics 2022;14:232. [DOI: 10.3390/pharmaceutics14020232] [Reference Citation Analysis]