{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:17:06Z","timestamp":1760242626371,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,12,5]],"date-time":"2017-12-05T00:00:00Z","timestamp":1512432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Twelfth five-year Education Science Plan Project of Hunan province of China","award":["XJK014AXX002"],"award-info":[{"award-number":["XJK014AXX002"]}]},{"name":"Scientific research project of Education Department of Hunan Province of China","award":["15C0696"],"award-info":[{"award-number":["15C0696"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The detection of composite miRNA functional module (CMFM) is of tremendous significance and helps in understanding the organization, regulation and execution of cell processes in cancer, but how to identify functional CMFMs is still a computational challenge. In this paper we propose a novel module detection method called MBCFM (detecting Composite Function Modules based on Maximal Biclique enumeration), specifically designed to bicluster miRNAs and target messenger RNAs (mRNAs) on the basis of multiple biological interaction information and topical network features. In this method, we employ algorithm MICA to enumerate all maximal bicliques and further extract R-pairs from the miRNA-mRNA regulatory network. Compared with two existing methods, Mirsynergy and SNMNMF on ovarian cancer dataset, the proposed method of MBCFM is not only able to extract cohesiveness-preserved CMFMs but also has high efficiency in running time. More importantly, MBCFM can be applied to detect other cancer-associated miRNA functional modules.<\/jats:p>","DOI":"10.3390\/a10040136","type":"journal-article","created":{"date-parts":[[2017,12,5]],"date-time":"2017-12-05T11:50:28Z","timestamp":1512474628000},"page":"136","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detecting Composite Functional Module in miRNA Regulation and mRNA Interaction Network"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2621-8027","authenticated-orcid":false,"given":"Yi","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Information Technology, Hunan Women\u2019s University, Changsha 410004, China"}]},{"given":"Chu","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.cell.2009.01.002","article-title":"Micrornas: Target recognition and regulatory functions","volume":"136","author":"Bartel","year":"2009","journal-title":"Cell"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1038\/nature03702","article-title":"Microrna expression profiles classify human cancers","volume":"435","author":"Lu","year":"2005","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2257","DOI":"10.1073\/pnas.0510565103","article-title":"A microrna expression signature of human solid tumors defines cancer gene targets","volume":"103","author":"Volinia","year":"2006","journal-title":"Proc. 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