{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:13:53Z","timestamp":1787008433201,"version":"build-2736575974"},"reference-count":59,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T00:00:00Z","timestamp":1604534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972423"],"award-info":[{"award-number":["61972423"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Graduate Research Innovation Project of Hunan","award":["CX20190125"],"award-info":[{"award-number":["CX20190125"]}]},{"name":"Hunan Provincial Science and Technology Program","award":["2018wk4001"],"award-info":[{"award-number":["2018wk4001"]}]},{"name":"111Project","award":["B18059"],"award-info":[{"award-number":["B18059"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>With the development of high-throughput technology and the accumulation of biomedical data, the prior information of biological entity can be calculated from different aspects. Specifically, drug\u2013drug similarities can be measured from target profiles, drug\u2013drug interaction and side effects. Similarly, different methods and data sources to calculate disease ontology can result in multiple measures of pairwise disease similarities. Therefore, in computational drug repositioning, developing a dynamic method to optimize the fusion process of multiple similarities is a crucial and challenging task. In this study, we propose a multi-similarities bilinear matrix factorization (MSBMF) method to predict promising drug-associated indications for existing and novel drugs. Instead of fusing multiple similarities into a single similarity matrix, we concatenate these similarity matrices of drug and disease, respectively. Applying matrix factorization methods, we decompose the drug\u2013disease association matrix into a drug-feature matrix and a disease-feature matrix. At the same time, using these feature matrices as basis, we extract effective latent features representing the drug and disease similarity matrices to infer missing drug\u2013disease associations. Moreover, these two factored matrices are constrained by non-negative factorization to ensure that the completed drug\u2013disease association matrix is biologically interpretable. In addition, we numerically solve the MSBMF model by an efficient alternating direction method of multipliers algorithm. The computational experiment results show that MSBMF obtains higher prediction accuracy than the state-of-the-art drug repositioning methods in cross-validation experiments. Case studies also demonstrate the effectiveness of our proposed method in practical applications. Availability: The data and code of MSBMF are freely available at https:\/\/github.com\/BioinformaticsCSU\/MSBMF. Corresponding author: Jianxin Wang, School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, P. R. China. E-mail: jxwang@mail.csu.edu.cn Supplementary Data: Supplementary data are available online at https:\/\/academic.oup.com\/bib.<\/jats:p>","DOI":"10.1093\/bib\/bbaa267","type":"journal-article","created":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T07:08:43Z","timestamp":1604473723000},"source":"Crossref","is-referenced-by-count":107,"title":["Computational drug repositioning based on multi-similarities bilinear matrix factorization"],"prefix":"10.1093","volume":"22","author":[{"given":"Mengyun","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaoyan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qichang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaohang","family":"Li","sequence":"additional","affiliation":[{"name":"Old Dominion University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianxin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,11,5]]},"reference":[{"issue":"7154","key":"2021072112311533900_ref1","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1038\/448645a","article-title":"New uses for old drugs","volume":"448","author":"Chong","year":"2007","journal-title":"Nature"},{"issue":"3","key":"2021072112311533900_ref2","doi-asserted-by":"crossref","first-page":"c125","DOI":"10.1159\/000232592","article-title":"Drug development: from concept to marketing!","volume":"113","author":"Tamimi","year":"2009","journal-title":"Nephron Clin Pract"},{"issue":"5","key":"2021072112311533900_ref3","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.tips.2013.03.004","article-title":"Challenges and opportunities of drug repositioning","volume":"34","author":"Novac","year":"2013","journal-title":"Trends Pharmacol Sci"},{"key":"2021072112311533900_ref4","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/nrd.2018.168","article-title":"Drug repurposing: progress, challenges and recommendations","volume":"18","author":"Pushpakom","year":"2019","journal-title":"Nat Rev Drug Discov"},{"key":"2021072112311533900_ref5","article-title":"Biomedical data and computational models for drug repositioning: a comprehensive review","author":"Luo","year":"2020","journal-title":"Brief Bioinform"},{"issue":"Database issue","key":"2021072112311533900_ref6","first-page":"D668","article-title":"DrugBank: a comprehensive resource for in silico drug discovery and exploration","volume":"34","year":"2006","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2021072112311533900_ref7","doi-asserted-by":"crossref","first-page":"D1202","DOI":"10.1093\/nar\/gkv951","article-title":"PubChem Substance and Compound Databases","volume":"44","year":"2016","journal-title":"Nucleic Acids Res"},{"issue":"Database issue","key":"2021072112311533900_ref8","first-page":"D1104","article-title":"The Comparative Toxicogenomics Database: update 2013","volume":"41","year":"2013","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2021072112311533900_ref9","doi-asserted-by":"crossref","first-page":"D1075","DOI":"10.1093\/nar\/gkv1075","article-title":"The SIDER database of drugs and side effects","volume":"44","year":"2016","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2021072112311533900_ref10","doi-asserted-by":"crossref","first-page":"D1071","DOI":"10.1093\/nar\/gku1011","article-title":"Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data","volume":"43","author":"Kibbe","year":"2015","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2021072112311533900_ref11","doi-asserted-by":"crossref","first-page":"D877","DOI":"10.1093\/nar\/gkw1012","article-title":"MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search","volume":"45","year":"2017","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"2021072112311533900_ref12","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1093\/nar\/30.1.52","article-title":"Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders","volume":"30","year":"2002","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2021072112311533900_ref13","doi-asserted-by":"crossref","first-page":"D833","DOI":"10.1093\/nar\/gkw943","article-title":"DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants","volume":"45","year":"2017","journal-title":"Nucleic Acids Res"},{"issue":"Database issue","key":"2021072112311533900_ref14","doi-asserted-by":"crossref","first-page":"D115","DOI":"10.1093\/nar\/gkh131","article-title":"UniProt: the universal protein knowledgebase","volume":"32","author":"Apweiler","year":"2004","journal-title":"Nucleic Acids Res"},{"issue":"Database issue","key":"2021072112311533900_ref15","first-page":"D535","article-title":"BioGRID: a general repository for interaction datasets","volume":"34","year":"2006","journal-title":"Nucleic Acids Res"},{"issue":"Database issue","key":"2021072112311533900_ref16","doi-asserted-by":"crossref","first-page":"D767","DOI":"10.1093\/nar\/gkn892","article-title":"Human protein reference database\u20132009 update","volume":"37","author":"Keshava Prasad","year":"2009","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"2021072112311533900_ref17","first-page":"D271","article-title":"The RCSB protein data bank: integrative view of protein, gene and 3D structural information","volume":"45","author":"Rose","year":"2017","journal-title":"Nucleic Acids Res"},{"issue":"17","key":"2021072112311533900_ref18","doi-asserted-by":"crossref","first-page":"2664","DOI":"10.1093\/bioinformatics\/btw228","article-title":"Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm","volume":"32","author":"Luo","year":"2016","journal-title":"Bioinformatics"},{"issue":"20","key":"2021072112311533900_ref19","doi-asserted-by":"crossref","first-page":"2923","DOI":"10.1093\/bioinformatics\/btu403","article-title":"Drug repositioning by integrating target information through a heterogeneous network model","volume":"30","author":"Wang","year":"2014","journal-title":"Bioinformatics"},{"issue":"1","key":"2021072112311533900_ref20","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.artmed.2014.11.003","article-title":"DrugNet: network-based drug-disease prioritization by integrating heterogeneous data","volume":"63","author":"Mart\u00ednez","year":"2015","journal-title":"Artif Intell Med"},{"issue":"Suppl 2","key":"2021072112311533900_ref21","article-title":"Inferring drug-disease associations based on known protein complexes","volume":"8","author":"Yu","year":"2015","journal-title":"BMC Med Genomics"},{"issue":"1","key":"2021072112311533900_ref22","article-title":"Drug repositioning: a machine-learning approach through data integration","volume":"5","author":"Napolitano","year":"2013","journal-title":"J Chem"},{"issue":"8","key":"2021072112311533900_ref23","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1093\/bioinformatics\/btw770","article-title":"LRSSL: predict and interpret drug-disease associations based on data integration using sparse subspace learning","volume":"33","author":"Liang","year":"2017","journal-title":"Bioinformatics"},{"issue":"19","key":"2021072112311533900_ref24","doi-asserted-by":"crossref","first-page":"3672","DOI":"10.1093\/bioinformatics\/btz156","article-title":"A new computational drug repurposing method using established disease-drug pair knowledge","volume":"35","author":"Saberian","year":"2019","journal-title":"Bioinformatics"},{"issue":"11","key":"2021072112311533900_ref25","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1093\/bioinformatics\/bty013","article-title":"Computational drug repositioning using low-rank matrix approximation and randomized algorithms","volume":"34","author":"Luo","year":"2018","journal-title":"Bioinformatics"},{"issue":"14","key":"2021072112311533900_ref26","doi-asserted-by":"crossref","first-page":"i455","DOI":"10.1093\/bioinformatics\/btz331","article-title":"Drug repositioning based on bounded nuclear norm regularization","volume":"35","author":"Yang","year":"2019","journal-title":"Bioinformatics (ISMB\/ECCB 2019)"},{"issue":"12","key":"2021072112311533900_ref27","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1007541","article-title":"Overlap matrix completion for predicting drug-associated indications","volume":"15","author":"Yang","year":"2019","journal-title":"PLoS Comput Biol"},{"issue":"2015","key":"2021072112311533900_ref28","article-title":"Matrix factorization-based prediction of novel drug indications by integrating genomic space","volume":"2015","year":"2015","journal-title":"Comput Math Methods Med"},{"issue":"1","key":"2021072112311533900_ref29","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/s12859-018-2575-6","article-title":"The computational prediction of drug-disease interactions using the dual-network ${L}_{2,1}$-CMF method","volume":"20","author":"Cui","year":"2019","journal-title":"BMC Bioinformatic"},{"issue":"20","key":"2021072112311533900_ref30","doi-asserted-by":"crossref","first-page":"4108","DOI":"10.1093\/bioinformatics\/btz182","article-title":"Drug repositioning through integration of prior knowledge and projections of drugs and diseases","volume":"35","author":"Xuan","year":"2019","journal-title":"Bioinformatics"},{"issue":"1","key":"2021072112311533900_ref31","doi-asserted-by":"crossref","DOI":"10.1186\/s12859-018-2220-4","article-title":"Predicting drug-disease associations by using similarity constrained matrix factorization","volume":"19","author":"Zhang","year":"2018","journal-title":"BMC Bioinformatics"},{"issue":"4","key":"2021072112311533900_ref32","doi-asserted-by":"crossref","first-page":"1956","DOI":"10.1137\/080738970","article-title":"A singular value thresholding algorithm for matrix completion","volume":"20","author":"Cai","year":"2008","journal-title":"SIAM Journal on Optimization"},{"key":"2021072112311533900_ref33","first-page":"53","article-title":"Drug target predictions based on heterogeneous graph inference","volume":"18","author":"Wang","year":"2013","journal-title":"Pac Symp Biocomput"},{"issue":"1","key":"2021072112311533900_ref34","doi-asserted-by":"crossref","first-page":"e1000641","DOI":"10.1371\/journal.pcbi.1000641","article-title":"Associating genes and protein complexes with disease via network propagation","volume":"6","author":"Vanunu","year":"2010","journal-title":"PLoS Comput Biol"},{"issue":"5","key":"2021072112311533900_ref35","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1038\/nmeth.1938","article-title":"Detecting overlapping protein complexes in protein-protein interaction networks","volume":"9","author":"Nepusz","year":"2012","journal-title":"Nat Methods"},{"issue":"Suppl 1","key":"2021072112311533900_ref36","article-title":"ProphNet: a generic prioritization method through propagation of information","volume":"15","author":"Mart\u00ednez","year":"2014","journal-title":"BMC Bioinformatics"},{"issue":"5","key":"2021072112311533900_ref37","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1038\/clpt.2009.103","article-title":"Systematic evaluation of drug-disease relationships to identify leads for novel drug uses","volume":"86","author":"Chiang","year":"2009","journal-title":"Clin Pharmacol Ther"},{"issue":"1","key":"2021072112311533900_ref38","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/nrg2918","article-title":"Network medicine: a network-based approach to human disease","volume":"12","author":"Barab\u00e1si","year":"2011","journal-title":"Nat Rev Genet"},{"issue":"13","key":"2021072112311533900_ref39","doi-asserted-by":"crossref","first-page":"i167","DOI":"10.1093\/bioinformatics\/btr213","article-title":"Uncover disease genes by maximizing information flow in the phenome-interactome network","volume":"27","author":"Chen","year":"2011","journal-title":"Bioinformatics"},{"issue":"1","key":"2021072112311533900_ref40","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1038\/msb.2011.26","article-title":"PREDICT: a method for inferring novel drug indications with application to personalized medicine","volume":"7","author":"Gottlieb","year":"2011","journal-title":"Mol Syst Biol"},{"issue":"21","key":"2021072112311533900_ref41","first-page":"493","article-title":"The chemistry development kit (CDK): an open-source java library for chemo-and bioinformatics","volume":"34","author":"Steinbeck","year":"2003","journal-title":"Chem"},{"issue":"1","key":"2021072112311533900_ref42","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1021\/ci00057a005","article-title":"SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules","volume":"28","author":"Weininger","year":"1988","journal-title":"J Chem Inf Comput Sci"},{"key":"2021072112311533900_ref43","article-title":"Using Information Content to Evaluate Semantic Similarity in a Taxonomy","volume-title":"IJCAI \u201895: Proceedings of the 14th International Joint Conference on Artificial Intelligence","author":"Resnik","year":"1995"},{"key":"2021072112311533900_ref44","first-page":"223","article-title":"Nouvelles recheres Sur la distribution florale","volume":"44","author":"Jaccard","year":"1908","journal-title":"Bull Soc Vaud Sci Nat"},{"issue":"5","key":"2021072112311533900_ref45","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1038\/sj.ejhg.5201585","article-title":"A text-mining analysis of the human phenome","volume":"14","year":"2006","journal-title":"Eur J Hum Genet"},{"issue":"10","key":"2021072112311533900_ref46","doi-asserted-by":"crossref","first-page":"1274","DOI":"10.1093\/bioinformatics\/btm087","article-title":"A new method to measure the semantic similarity of GO terms","volume":"23","author":"Wang","year":"2007","journal-title":"Bioinformatics"},{"issue":"15","key":"2021072112311533900_ref47","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1093\/bioinformatics\/btl190","article-title":"Independent component analysis-based penalized discriminant method for tumor classification using gene expression data","volume":"22","author":"Huang","year":"2006","journal-title":"Bioinformatics"},{"issue":"8","key":"2021072112311533900_ref48","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MC.2009.263","article-title":"Matrix factorization techniques for recommender systems","volume":"42","author":"Koren","year":"2009","journal-title":"Computer"},{"issue":"9","key":"2021072112311533900_ref49","doi-asserted-by":"crossref","first-page":"2605","DOI":"10.1162\/neco.2009.03-08-722","article-title":"A model for learning topographically organized parts-based representations of objects in visual cortex: topographic nonnegative matrix factorization","volume":"21","author":"Hosoda","year":"2009","journal-title":"Neural Comput"},{"issue":"11","key":"2021072112311533900_ref50","doi-asserted-by":"crossref","first-page":"2293","DOI":"10.1016\/j.ins.2011.01.029","article-title":"Enhanced clustering of biomedical documents using ensemble non-negative matrix factorization","volume":"181","author":"Huang","year":"2011","journal-title":"Inform Sci"},{"issue":"2","key":"2021072112311533900_ref51","first-page":"111","article-title":"Positive matrix factorization: a non-negative factor model with optimal utilization of error estimates of data values","volume":"5","author":"Paatero","year":"1994","journal-title":"Environ"},{"key":"2021072112311533900_ref52","first-page":"556","article-title":"Algorithms for non-negative matrix factorization","volume":"13","author":"Lee","year":"2001","journal-title":"Adv Neural Inf Process Syst"},{"issue":"1","key":"2021072112311533900_ref53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","article-title":"Distributed optimization and statistical learning via the alternating direction method of multipliers","volume":"3","author":"Boyd","year":"2010","journal-title":"Found Trends Mach Learn"},{"issue":"281","key":"2021072112311533900_ref54","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1090\/S0025-5718-2012-02598-1","article-title":"Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization","volume":"82","author":"Yang","year":"2012","journal-title":"Math Comput"},{"issue":"2","key":"2021072112311533900_ref55","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/s11464-012-0194-5","article-title":"An alternating direction algorithm for matrix completion with nonnegative factors","volume":"7","author":"Xu","year":"2012","journal-title":"Front Math China"},{"key":"2021072112311533900_ref56","article-title":"An alternating direction algorithm for nonnegative matrix factorization","author":"Zhang","year":"2010","journal-title":"CAAM Technical Reports"},{"key":"2021072112311533900_ref57","article-title":"Collaborative Matrix Factorization with Multiple Similarities for Predicting Drug-Target Interactions","volume-title":"Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","year":"2013"},{"issue":"9","key":"2021072112311533900_ref58","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.1109\/TPAMI.2017.2748590","article-title":"Bilinear factor matrix norm minimization for robust PCA: algorithms and applications","volume":"40","author":"Shang","year":"2018","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"2021072112311533900_ref59","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/nmeth.2810","article-title":"Similarity network fusion for aggregating data types on a genomic scale","volume":"11","author":"Wang","year":"2014","journal-title":"Nat Methods"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/22\/4\/bbaa267\/39144030\/bbaa267.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/22\/4\/bbaa267\/39144030\/bbaa267.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T07:16:22Z","timestamp":1697008582000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbaa267\/5956157"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,5]]},"references-count":59,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,7,20]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbaa267","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2021,7]]},"published":{"date-parts":[[2020,11,5]]},"article-number":"bbaa267"}}