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Cited by in F6Publishing
For: Murali V, Königs C, Deekshitula S, Nukala S, Santhi MD, Athri P. CompoundDB4j: Integrated Drug Resource of Heterogeneous Chemical Databases. Mol Inf 2020;39:2000013. [DOI: 10.1002/minf.202000013] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Murali V, Muralidhar YP, Königs C, Nair M, Madhu S, Nedungadi P, Srinivasa G, Athri P. Predicting clinical trial outcomes using drug bioactivities through graph database integration and machine learning. Chem Biol Drug Des 2022. [PMID: 35587730 DOI: 10.1111/cbdd.14092] [Reference Citation Analysis]
2 Gimadiev T, Nugmanov R, Batyrshin D, Madzhidov T, Maeda S, Sidorov P, Varnek A. Combined Graph/Relational Database Management System for Calculated Chemical Reaction Pathway Data. J Chem Inf Model 2021;61:554-9. [PMID: 33502186 DOI: 10.1021/acs.jcim.0c01280] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
3 Shankar S, Bhandari I, Okou DT, Srinivasa G, Athri P. Predicting adverse drug reactions of two-drug combinations using structural and transcriptomic drug representations to train an artificial neural network. Chem Biol Drug Des 2021;97:665-73. [PMID: 33006799 DOI: 10.1111/cbdd.13802] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
4 Shankar S, Bhandari I, Okou DT, Srinivasa G, Athri P. Predicting Adverse Drug Reactions of Two-drug Combinations using Structural and Transcriptomic Drug Representations to Train a Artificial Neural Network.. [DOI: 10.1101/2020.06.30.176016] [Reference Citation Analysis]