{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:46Z","timestamp":1772138086916,"version":"3.50.1"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2018,2,27]],"date-time":"2018-02-27T00:00:00Z","timestamp":1519689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61272152"],"award-info":[{"award-number":["61272152"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61472333"],"award-info":[{"award-number":["61472333"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772441"],"award-info":[{"award-number":["61772441"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11622538"],"award-info":[{"award-number":["11622538"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673150"],"award-info":[{"award-number":["61673150"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"European project funded","award":["FP7\u2013FET 612146"],"award-info":[{"award-number":["FP7\u2013FET 612146"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LR16A050001"],"award-info":[{"award-number":["LR16A050001"]}]},{"name":"Juan de la Cierva position","award":["IJCI-2015-26991"],"award-info":[{"award-number":["IJCI-2015-26991"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>The identification of disease-related microRNAs (miRNAs) is an essential but challenging task in bioinformatics research. Similarity-based link prediction methods are often used to predict potential associations between miRNAs and diseases. In these methods, all unobserved associations are ranked by their similarity scores. Higher score indicates higher probability of existence. However, most previous studies mainly focus on designing advanced methods to improve the prediction accuracy while neglect to investigate the link predictability of the networks that present the miRNAs and diseases associations. In this work, we construct a bilayer network by integrating the miRNA\u2013disease network, the miRNA similarity network and the disease similarity network. We use structural consistency as an indicator to estimate the link predictability of the related networks. On the basis of the indicator, a derivative algorithm, called structural perturbation method (SPM), is applied to predict potential associations between miRNAs and diseases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The link predictability of bilayer network is higher than that of miRNA\u2013disease network, indicating that the prediction of potential miRNAs\u2013diseases associations on bilayer network can achieve higher accuracy than based merely on the miRNA\u2013disease network. A comparison between the SPM and other algorithms reveals the reliable performance of SPM which performed well in a 5-fold cross-validation. We test fifteen networks. The AUC values of SPM are higher than some well-known methods, indicating that SPM could serve as a useful computational method for improving the identification accuracy of miRNA\u2012disease associations. Moreover, in a case study on breast neoplasm, 80% of the top-20 predicted miRNAs have been manually confirmed by previous experimental studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>https:\/\/github.com\/lecea\/SPM-code.git<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty112","type":"journal-article","created":{"date-parts":[[2018,2,24]],"date-time":"2018-02-24T07:08:40Z","timestamp":1519456120000},"page":"2425-2432","source":"Crossref","is-referenced-by-count":212,"title":["Prediction of potential disease-associated microRNAs using structural perturbation method"],"prefix":"10.1093","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1081-7658","authenticated-orcid":false,"given":"Xiangxiang","family":"Zeng","sequence":"first","affiliation":[{"name":"Department of Computer Science, Xiamen University, Xiamen, China"},{"name":"Department of Artificial Intelligence, Universidad Polit\u00e9cnica de Madrid (UPM) Campus Montegancedo s\/n, Boadilla del Monte, Madrid, Spain"}]},{"given":"Li","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Xiamen University, Xiamen, China"}]},{"given":"Linyuan","family":"L\u00fc","sequence":"additional","affiliation":[{"name":"Alibaba Research Center for Complexity Sciences, Alibaba Business College, Hangzhou Normal University, Hangzhou, China"},{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China"}]},{"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Tianjin University, Tianjin, China"}]}],"member":"286","published-online":{"date-parts":[[2018,2,27]]},"reference":[{"key":"2023012713011972700_bty112-B1","doi-asserted-by":"crossref","first-page":"4653","DOI":"10.1242\/dev.02073","article-title":"MicroRNA functions in animal development and human disease","volume":"132","author":"Alvarez-Garcia","year":"2005","journal-title":"Development"},{"key":"2023012713011972700_bty112-B2","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1038\/nature02871","article-title":"The functions of animal microRNAs","volume":"431","author":"Ambros","year":"2004","journal-title":"Nature"},{"key":"2023012713011972700_bty112-B3","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/S0092-8674(04)00045-5","article-title":"MicroRNAs: genomics, biogenesis, mechanism, and function","volume":"116","author":"Bartel","year":"2004","journal-title":"Cell"},{"key":"2023012713011972700_bty112-B4","doi-asserted-by":"crossref","first-page":"2792","DOI":"10.1039\/c2mb25180a","article-title":"RWRMDA: predicting novel human microRNA\u2013disease associations","volume":"8","author":"Chen","year":"2012","journal-title":"Mol. 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