Drug repositioning by integrating target information through a heterogeneous network model

Wenhui Wang, Sen Yang, Xiang Zhang, Jing Li

Research output: Contribution to journalArticlepeer-review

121 Scopus citations

Abstract

MOTIVATION: The emergence of network medicine not only offers more opportunities for better and more complete understanding of the molecular complexities of diseases, but also serves as a promising tool for identifying new drug targets and establishing new relationships among diseases that enable drug repositioning. Computational approaches for drug repositioning by integrating information from multiple sources and multiple levels have the potential to provide great insights to the complex relationships among drugs, targets, disease genes and diseases at a system level.

RESULTS: In this article, we have proposed a computational framework based on a heterogeneous network model and applied the approach on drug repositioning by using existing omics data about diseases, drugs and drug targets. The novelty of the framework lies in the fact that the strength between a disease-drug pair is calculated through an iterative algorithm on the heterogeneous graph that also incorporates drug-target information. Comprehensive experimental results show that the proposed approach significantly outperforms several recent approaches. Case studies further illustrate its practical usefulness.

AVAILABILITY AND IMPLEMENTATION: http://cbc.case.edu

CONTACT: jingli@cwru.edu

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)2923-2930
Number of pages8
JournalBioinformatics (Oxford, England)
Volume30
Issue number20
DOIs
StatePublished - Oct 15 2014

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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