{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T11:29:42Z","timestamp":1763810982486,"version":"3.41.2"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Natural Science Foundation of Xinjiang Uygur Autonomous Region","award":["2021D01D05"],"award-info":[{"award-number":["2021D01D05"]}]},{"name":"Tianshan Youth Project\u2013Outstanding Youth Science and Technology Talents of Xinjiang","award":["2020Q005"],"award-info":[{"award-number":["2020Q005"]}]},{"name":"Pioneer Hundred Talents Program of Chinese Academy of Sciences"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>As microRNAs (miRNAs) are involved in many essential biological processes, their abnormal expressions can serve as biomarkers and prognostic indicators to prevent the development of complex diseases, thus providing accurate early detection and prognostic evaluation. Although a number of computational methods have been proposed to predict miRNA\u2013disease associations (MDAs) for further experimental verification, their performance is limited primarily by the inadequacy of exploiting lower order patterns characterizing known MDAs to identify missing ones from MDA networks. Hence, in this work, we present a novel prediction model, namely HiSCMDA, by incorporating higher order network structures for improved performance of MDA prediction. To this end, HiSCMDA first integrates miRNA similarity network, disease similarity network and MDA network to preserve the advantages of all these networks. After that, it identifies overlapping functional modules from the integrated network by predefining several higher order connectivity patterns of interest. Last, a path-based scoring function is designed to infer potential MDAs based on network paths across related functional modules. HiSCMDA yields the best performance across all datasets and evaluation metrics in the cross-validation and independent validation experiments. Furthermore, in the case studies, 49 and 50 out of the top 50 miRNAs, respectively, predicted for colon neoplasms and lung neoplasms have been validated by well-established databases. Experimental results show that rich higher order organizational structures exposed in the MDA network gain new insight into the MDA prediction based on higher order connectivity patterns.<\/jats:p>","DOI":"10.1093\/bib\/bbac562","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T15:14:05Z","timestamp":1671808445000},"source":"Crossref","is-referenced-by-count":16,"title":["Incorporating higher order network structures to improve miRNA\u2013disease association prediction based on functional modularity"],"prefix":"10.1093","volume":"24","author":[{"given":"Yizhou","family":"He","sequence":"first","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Wuhan University of Technology , Wuhan, 430070 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Wuhan University of Technology , Wuhan, 430070 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaorui","family":"Su","sequence":"additional","affiliation":[{"name":"Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences , Urumqi, 830011 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bowei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences , Urumqi, 830011 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengwu","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Wuhan University of Technology , Wuhan, 430070 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1591-8549","authenticated-orcid":false,"given":"Lun","family":"Hu","sequence":"additional","affiliation":[{"name":"Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences , Urumqi, 830011 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"issue":"4","key":"2023011917083284600_ref1","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/S1672-0229(08)60044-3","article-title":"A brief review on the mechanisms of mirna regulation","volume":"7","author":"Cai","year":"2009","journal-title":"Genomics Proteomics Bioinformatics"},{"issue":"1","key":"2023011917083284600_ref2","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1093\/jb\/mvz079","article-title":"Mir-146a promoted breast cancer proliferation and invasion by regulating nm23-h1","volume":"167","author":"Chen","year":"2020","journal-title":"The Journal of Biochemistry"},{"issue":"1","key":"2023011917083284600_ref3","first-page":"764","article-title":"Expression and clinical significance of mirna-145 and mirna-218 in laryngeal cancer","volume":"18","author":"Guo","year":"2019","journal-title":"Oncol Lett"},{"issue":"1","key":"2023011917083284600_ref4","first-page":"1","article-title":"Wbsmda: within and between score for mirna-disease association prediction","volume":"6","author":"Chen","year":"2016","journal-title":"Sci Rep"},{"issue":"6","key":"2023011917083284600_ref5","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1039\/C6MB00853D","article-title":"A novel computational model based on super-disease and mirna for potential mirna\u2013disease association prediction","volume":"13","author":"Chen","year":"2017","journal-title":"Mol Biosyst"},{"key":"2023011917083284600_ref6","doi-asserted-by":"crossref","first-page":"385","DOI":"10.3389\/fgene.2019.00385","article-title":"Bipartite heterogeneous network method based on co-neighbor for mirna-disease association prediction","volume":"10","author":"Chen","year":"2019","journal-title":"Front Genet"},{"issue":"3","key":"2023011917083284600_ref7","doi-asserted-by":"crossref","first-page":"e1005455","DOI":"10.1371\/journal.pcbi.1005455","article-title":"Pbmda: a novel and effective path-based computational model for mirna-disease association prediction","volume":"13","author":"You","year":"2017","journal-title":"PLoS Comput Biol"},{"issue":"1","key":"2023011917083284600_ref8","first-page":"1","article-title":"Inferring microrna-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network","volume":"9","author":"Dong-Ling","year":"2019","journal-title":"Sci Rep"},{"issue":"3","key":"2023011917083284600_ref9","doi-asserted-by":"crossref","first-page":"e1006865","DOI":"10.1371\/journal.pcbi.1006865","article-title":"Lmtrda: using logistic model tree to predict mirna-disease associations by fusing multi-source information of sequences and similarities","volume":"15","author":"Wang","year":"2019","journal-title":"PLoS Comput Biol"},{"issue":"1","key":"2023011917083284600_ref10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-63735-9","article-title":"Predicting mirna-disease association from heterogeneous information network with grarep embedding model","volume":"10","author":"Ji","year":"2020","journal-title":"Sci Rep"},{"issue":"22","key":"2023011917083284600_ref11","doi-asserted-by":"crossref","first-page":"4730","DOI":"10.1093\/bioinformatics\/btz297","article-title":"Adaptive boosting-based computational model for predicting potential mirna-disease associations","volume":"35","author":"Zhao","year":"2019","journal-title":"Bioinformatics"},{"issue":"8","key":"2023011917083284600_ref12","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1093\/bioinformatics\/btz965","article-title":"Neural inductive matrix completion with graph convolutional networks for mirna-disease association prediction","volume":"36","author":"Li","year":"2020","journal-title":"Bioinformatics"},{"issue":"2","key":"2023011917083284600_ref13","doi-asserted-by":"crossref","first-page":"bbac021","DOI":"10.1093\/bib\/bbac021","article-title":"Prediction of potential mirna\u2013disease associations based on stacked autoencoder","volume":"23","author":"Wang","year":"2022","journal-title":"Brief Bioinform"},{"issue":"6295","key":"2023011917083284600_ref14","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1126\/science.aad9029","article-title":"Higher-order organization of complex networks","volume":"353","author":"Benson","year":"2016","journal-title":"Science"},{"issue":"2","key":"2023011917083284600_ref15","doi-asserted-by":"crossref","first-page":"207","DOI":"10.3233\/ICA-200645","article-title":"Exploiting higher-order patterns for community detection in attributed graphs","volume":"28","author":"Lun","year":"2021","journal-title":"Integrated Computer-Aided Engineering"},{"issue":"2","key":"2023011917083284600_ref16","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.cell.2010.09.050","article-title":"Snapshot: network motifs","volume":"143","author":"Shoval","year":"2010","journal-title":"Cell"},{"issue":"3","key":"2023011917083284600_ref17","doi-asserted-by":"crossref","first-page":"e31929","DOI":"10.1371\/journal.pone.0031929","article-title":"Hierarchical information clustering by means of topologically embedded graphs","volume":"7","author":"Song","year":"2012","journal-title":"PLoS One"},{"issue":"4","key":"2023011917083284600_ref18","doi-asserted-by":"crossref","first-page":"102092","DOI":"10.1016\/j.jogoh.2021.102092","article-title":"Circulating serum mir-200c and mir-34a-5p as diagnostic biomarkers for endometriosis","volume":"50","author":"Misir","year":"2021","journal-title":"Journal of Gynecology Obstetrics and Human Reproduction"},{"issue":"13","key":"2023011917083284600_ref19","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1093\/bioinformatics\/btq241","article-title":"Inferring the human microrna functional similarity and functional network based on microrna-associated diseases","volume":"26","author":"Wang","year":"2010","journal-title":"Bioinformatics"},{"issue":"4","key":"2023011917083284600_ref20","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1093\/bioinformatics\/btaa775","article-title":"Hiscf: leveraging higher-order structures for clustering analysis in biological networks","volume":"37","author":"Lun","year":"2021","journal-title":"Bioinformatics"},{"issue":"9","key":"2023011917083284600_ref21","doi-asserted-by":"crossref","first-page":"3473","DOI":"10.1109\/TFUZZ.2021.3117442","article-title":"A fast fuzzy clustering algorithm for complex networks via a generalized momentum method","volume":"30","author":"Lun","year":"2022","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"1","key":"2023011917083284600_ref22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-021-27138-2","article-title":"Network medicine for disease module identification and drug repurposing with the nedrex platform","volume":"12","author":"Sadegh","year":"2021","journal-title":"Nat Commun"},{"issue":"D1","key":"2023011917083284600_ref23","doi-asserted-by":"crossref","first-page":"D1070","DOI":"10.1093\/nar\/gkt1023","article-title":"Hmdd v2. 0: a database for experimentally supported human microrna and disease associations","volume":"42","author":"Li","year":"2014","journal-title":"Nucleic Acids Res"},{"issue":"8","key":"2023011917083284600_ref24","doi-asserted-by":"crossref","first-page":"e70204","DOI":"10.1371\/journal.pone.0070204","article-title":"Prediction of micrornas associated with human diseases based on weighted k most similar neighbors","volume":"8","author":"Xuan","year":"2013","journal-title":"PLoS One"},{"issue":"21","key":"2023011917083284600_ref25","doi-asserted-by":"crossref","first-page":"3036","DOI":"10.1093\/bioinformatics\/btr500","article-title":"Gaussian interaction profile kernels for predicting drug\u2013target interaction","volume":"27","author":"Van Laarhoven","year":"2011","journal-title":"Bioinformatics"},{"issue":"20","key":"2023011917083284600_ref26","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1093\/bioinformatics\/btt426","article-title":"Novel human lncrna\u2013disease association inference based on lncrna expression profiles","volume":"29","author":"Chen","year":"2013","journal-title":"Bioinformatics"},{"key":"2023011917083284600_ref27","article-title":"General tensor spectral co-clustering for higher-order data","volume":"29","author":"Tao","year":"2016","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"2","key":"2023011917083284600_ref28","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1137\/16M1074023","article-title":"The spacey random walk: a stochastic process for higher-order data","volume":"59","author":"Benson","year":"2017","journal-title":"SIAM Review"},{"article-title":"k-means++: The advantages of careful seeding","volume-title":"Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms","author":"Arthur","key":"2023011917083284600_ref29"},{"issue":"suppl_1","key":"2023011917083284600_ref30","doi-asserted-by":"crossref","first-page":"D98","DOI":"10.1093\/nar\/gkn714","article-title":"mir2disease: a manually curated database for microrna deregulation in human disease","volume":"37","author":"Jiang","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"2023011917083284600_ref31","article-title":"Dbdemc 3.0: functional exploration of differentially expressed mirnas in cancers of human and model organisms","author":"Feng","year":"2022","journal-title":"Genomics Proteomics Bioinformatics"},{"issue":"1","key":"2023011917083284600_ref32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.14740\/gr1239","article-title":"Colon cancer: a clinician\u2019s perspective in 2019","volume":"13","author":"Ahmed","year":"2020","journal-title":"Gastroenterology Res"},{"issue":"13","key":"2023011917083284600_ref33","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1016\/S1470-2045(13)70491-1","article-title":"Prognostic and predictive value of a microrna signature in stage ii colon cancer: a microrna expression analysis","volume":"14","author":"Jia-Xing Zhang","year":"2013","journal-title":"Lancet Oncol"},{"issue":"1","key":"2023011917083284600_ref34","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s12079-021-00612-8","article-title":"Identification of key regulators associated with colon cancer prognosis and pathogenesis","volume":"16","author":"Toolabi","year":"2022","journal-title":"Journal of cell communication and signaling"},{"issue":"8","key":"2023011917083284600_ref35","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1517\/14728222.2015.1057569","article-title":"Mir-199a-5p and mir-375 affect colon cancer cell sensitivity to cetuximab by targeting phlpp1","volume":"19","author":"Mussnich","year":"2015","journal-title":"Expert Opin Ther Targets"},{"issue":"1","key":"2023011917083284600_ref36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s42003-020-0863-y","article-title":"A mirna-based diagnostic model predicts resectable lung cancer in humans with high accuracy","volume":"3","author":"Asakura","year":"2020","journal-title":"Communications biology"},{"issue":"1","key":"2023011917083284600_ref37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12943-021-01469-6","article-title":"Lncrna pkmyt1ar promotes cancer stem cell maintenance in non-small cell lung cancer via activating wnt signaling pathway","volume":"20","author":"He","year":"2021","journal-title":"Mol Cancer"},{"issue":"1","key":"2023011917083284600_ref38","first-page":"1","article-title":"Radiation-induced mir-208a increases the proliferation and radioresistance by targeting p21 in human lung cancer cells","volume":"35","author":"Tang","year":"2016","journal-title":"J Exp Clin Cancer Res"},{"issue":"1","key":"2023011917083284600_ref39","doi-asserted-by":"crossref","first-page":"bbab515","DOI":"10.1093\/bib\/bbab515","article-title":"Hingrl: predicting drug\u2013disease associations with graph representation learning on heterogeneous information networks","volume":"23","author":"Zhao","year":"2022","journal-title":"Brief Bioinform"},{"issue":"3","key":"2023011917083284600_ref40","doi-asserted-by":"crossref","first-page":"bbac140","DOI":"10.1093\/bib\/bbac140","article-title":"Attention-based knowledge graph representation learning for predicting drug-drug interactions","volume":"23","author":"Xiaorui","year":"2022","journal-title":"Brief Bioinform"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbac562\/48782205\/bbac562.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbac562\/48782205\/bbac562.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T17:15:33Z","timestamp":1674148533000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac562\/6958503"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,23]]},"references-count":40,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1,19]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbac562","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"type":"print","value":"1467-5463"},{"type":"electronic","value":"1477-4054"}],"subject":[],"published-other":{"date-parts":[[2023,1]]},"published":{"date-parts":[[2022,12,23]]},"article-number":"bbac562"}}