title: Network-based inference methods for drug repositioning.
abstract: Mining potential drug-disease associations can speed up drug repositioning for pharmaceutical companies. Previous computational strategies focused on prior biological information for association inference. However, such information may not be comprehensively available and may contain errors. Different from previous research, two inference methods, ProbS and HeatS, were introduced in this paper to predict direct drug-disease associations based only on the basic network topology measure. Bipartite network topology was used to prioritize the potentially indicated diseases for a drug. Experimental results showed that both methods can receive reliable prediction performance and achieve AUC values of 0.9192 and 0.9079, respectively. Case studies on real drugs indicated that some of the strongly predicted associations were confirmed by results in the Comparative Toxicogenomics Database (CTD). Finally, a comprehensive prediction of drug-disease associations enables us to suggest many new drug indications for further studies.
authors.affiliation: School of Software, East China Jiaotong University, Nanchang 330013, China.
authors.forename: Hailin
authors.identifier: 0000-0002-5119-4517
authors.initials: H
authors.lastname: Chen
authors.affiliation: School of Information Engineering, East China Jiaotong University, Nanchang 330013, China.
authors.forename: Heng
authors.initials: H
authors.lastname: Zhang
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors.forename: Zuping
authors.identifier: 0000-0001-6169-9191
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: School of Software, East China Jiaotong University, Nanchang 330013, China.
authors.forename: Yiqin
authors.initials: Y
authors.lastname: Cao
authors.affiliation: School of Software, East China Jiaotong University, Nanchang 330013, China.
authors.forename: Wenliang
authors.initials: W
authors.lastname: Tang
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001241:Aspirin / Q000737:chemistry; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D016208:Databases, Factual; D058492:Drug Repositioning / Q000295:instrumentation* / Q000379:methods*; D015736:Felodipine / Q000737:chemistry; D006801:Humans; D015233:Models, Statistical; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012984:Software; D013629:Tamoxifen / Q000737:chemistry
chemical_list: D004364:Pharmaceutical Preparations; D013629:Tamoxifen; D015736:Felodipine; D001241:Aspirin