ChemDIS: A chemical-disease inference system based on chemical-protein interactions

Chun Wei Tung

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


Background: The 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. Results: 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 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. Conclusions: ChemDIS 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

Original languageEnglish
Article number25
JournalJournal of Cheminformatics
Issue number1
Publication statusPublished - Jun 15 2015
Externally publishedYes


  • Chemical-disease inference
  • Chemical-protein interaction
  • Disease ontology
  • Enrichment analysis
  • Gene ontology

ASJC Scopus subject areas

  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Computer Graphics and Computer-Aided Design
  • Library and Information Sciences


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