Abstract
BackgroundThe characterization of toxicities associated with environmental and industrial chemicals is required for risk assessment. However, we lack the toxicological data for a large portion of chemicals due to the high cost of experiments for a huge number of chemicals. The development of computational methods for identifying potential risks associated with chemicals is desirable for generating testable hypothesis to accelerate the hazard identification process.ResultsA chemical–disease inference system named ChemDIS was developed to facilitate hazard identification for chemicals. The chemical–protein interactions from a large database STITCH and protein–disease relationship from disease ontology and disease ontology lite were utilized for chemical–protein–disease inferences. Tools with user-friendly interfaces for enrichment analysis of functions, pathways and diseases were implemented and integrated into ChemDIS. An analysis on maleic acid and sibutramine showed that ChemDIS could be a useful tool for the identification of potential functions, pathways and diseases affected by poorly characterized chemicals.ConclusionsChemDIS is an integrated chemical–disease inference system for poorly characterized chemicals with potentially affected functions and pathways for experimental validation. ChemDIS server is freely accessible at http://cwtung.kmu.edu.tw/chemdis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0077-3) contains supplementary material, which is available to authorized users.
Highlights
The characterization of toxicities associated with environmental and industrial chemicals is required for risk assessment
In order to facilitate the inferences of functions, pathways and diseases affected by various environmental and industrial chemicals, a comprehensive resource named ChemDIS was constructed by integrating the chemical–protein interactions in human from STITCH database and enrichment analysis tools
ChemDIS ChemDIS provides a unique resource for inferring functions, pathways and diseases associated with chemicals based on chemical–protein interactions
Summary
A chemical–disease inference system named ChemDIS was developed to facilitate hazard identification for chemicals. The chemical–protein interactions from a large database STITCH and protein–disease relationship from disease ontology and disease ontology lite were utilized for chemical–protein–disease inferences. Tools with userfriendly interfaces for enrichment analysis of functions, pathways and diseases were implemented and integrated into ChemDIS. An analysis on maleic acid and sibutramine showed that ChemDIS could be a useful tool for the identifica‐ tion of potential functions, pathways and diseases affected by poorly characterized chemicals
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