title: Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm.
abstract: Drug repositioning, which aims to identify new indications for existing drugs, offers a promising alternative to reduce the total time and cost of traditional drug development. Many computational strategies for drug repositioning have been proposed, which are based on similarities among drugs and diseases. Current studies typically use either only drug-related properties (e.g. chemical structures) or only disease-related properties (e.g. phenotypes) to calculate drug or disease similarity, respectively, while not taking into account the influence of known drug-disease association information on the similarity measures.
  
  
  
  In this article, based on the assumption that similar drugs are normally associated with similar diseases and vice versa, we propose a novel computational method named MBiRW, which utilizes some comprehensive similarity measures and Bi-Random walk (BiRW) algorithm to identify potential novel indications for a given drug. By integrating drug or disease features information with known drug-disease associations, the comprehensive similarity measures are firstly developed to calculate similarity for drugs and diseases. Then drug similarity network and disease similarity network are constructed, and they are incorporated into a heterogeneous network with known drug-disease interactions. Based on the drug-disease heterogeneous network, BiRW algorithm is adopted to predict novel potential drug-disease associations. Computational experiment results from various datasets demonstrate that the proposed approach has reliable prediction performance and outperforms several recent computational drug repositioning approaches. Moreover, case studies of five selected drugs further confirm the superior performance of our method to discover potential indications for drugs practically.
  
  
  
  http://github.com//bioinfomaticsCSU/MBiRW CONTACT: jxwang@mail.csu.edu.cn
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Information Science and Engineering, Central South University, ChangSha, 410083, China School of Computer and Information Engineering, Henan University, KaiFeng 475001, China.
authors.forename: Huimin
authors.initials: H
authors.lastname: Luo
authors.affiliation: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors.forename: Jianxin
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors.forename: Min
authors.initials: M
authors.lastname: Li
authors.affiliation: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors.forename: Junwei
authors.initials: J
authors.lastname: Luo
authors.affiliation: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors.forename: Xiaoqing
authors.initials: X
authors.lastname: Peng
authors.affiliation: Division of Biomedical Engineering, University of Saskatchewan, Saskatchewan S7N 5A9, Canada.
authors.forename: Fang-Xiang
authors.initials: FX
authors.lastname: Wu
authors.affiliation: Department of Computer Science, Georgia State University, Atlanta, GA 30302-3994, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D058492:Drug Repositioning; D008962:Models, Theoretical