Drug repositioning by integrating target information through a heterogeneous network model

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 dr...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) Vol. 30; no. 20; pp. 2923 - 2930
Main Authors: Wang, Wenhui, Yang, Sen, Zhang, Xiang, Li, Jing
Format: Journal Article
Language:English
Published: England Oxford University Press 15.10.2014
Subjects:
Algorithms
Computational Biology - methods
Disease
Drug Repositioning - methods
Humans
Models, Theoretical
Molecular Targeted Therapy
Original Papers
Pharmaceutical Preparations
ISSN:1367-4803, 1367-4811, 1367-4811
Online Access:Get full text
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Summary: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.
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Associate Editor: Igor Jurisica
ISSN:1367-4803
1367-4811
1367-4811
DOI:10.1093/bioinformatics/btu403