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DIGEP-Pred: web service for in silico prediction of drug-induced gene expression profiles based on structural formula
Author(s) -
Alexey A. Lagunin,
Sergey M. Ivanov,
Anastasia V. Rudik,
Dmitry Filimonov,
Vladimir Poroikov
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt322
Subject(s) - toxicogenomics , in silico , drug , gene expression , computational biology , gene , data mining , computer science , service (business) , web service , expression (computer science) , software , web application , database , bioinformatics , biology , pharmacology , genetics , world wide web , economy , economics , programming language
Experimentally found gene expression profiles are used to solve different problems in pharmaceutical studies, such as drug repositioning, resistance, toxicity and drug-drug interactions. A special web service, DIGEP-Pred, for prediction of drug-induced changes of gene expression profiles based on structural formulae of chemicals has been developed. Structure-activity relationships for prediction of drug-induced gene expression profiles were determined by Prediction of Activity Spectra for Substances (PASS) software. Comparative Toxicogenomics Database with data on the known drug-induced gene expression profiles of chemicals was used to create mRNA- and protein-based training sets. An average prediction accuracy for the training sets (ROC AUC) calculated by leave-one-out cross-validation on the basis of mRNA data (1385 compounds, 952 genes, 500 up- and 475 down-regulations) and protein data (1451 compounds, 139 genes, 93 up- and 55 down-regulations) exceeded 0.85.

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