Developments in Toxicogenomics: Understanding and Predicting Compound-induced Toxicity from Gene Expression Data

Overview

Journal Mol Omics

Publisher Royal Society of Chemistry

Specialties Biochemistry
Biology
Molecular Biology

Date 2018 Jun 20

PMID 29917034

Citations 42

Authors

Benjamin Alexander-Dann

Lavinia Lorena Pruteanu

Erin Oerton

Nitin Sharma

Ioana Berindan-Neagoe

Dezso Modos

Andreas Bender

Affiliations

Soon will be listed here.

Abstract

The toxicogenomics field aims to understand and predict toxicity by using 'omics' data in order to study systems-level responses to compound treatments. In recent years there has been a rapid increase in publicly available toxicological and 'omics' data, particularly gene expression data, and a corresponding development of methods for its analysis. In this review, we summarize recent progress relating to the analysis of RNA-Seq and microarray data, review relevant databases, and highlight recent applications of toxicogenomics data for understanding and predicting compound toxicity. These include the analysis of differentially expressed genes and their enrichment, signature matching, methods based on interaction networks, and the analysis of co-expression networks. In the future, these state-of-the-art methods will likely be combined with new technologies, such as whole human body models, to produce a comprehensive systems-level understanding of toxicity that reduces the necessity of in vivo toxicity assessment in animal models.

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