{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:02:28Z","timestamp":1767830548121,"version":"3.49.0"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: MicroRNAs (miRNAs) and mRNAs constitute an important part of gene regulatory networks, influencing diverse biological phenomena. Elucidating closely related miRNAs and mRNAs can be an essential first step towards the discovery of their combinatorial effects on different cellular states. Here, we propose a probabilistic learning method to identify synergistic miRNAs involving regulation of their condition-specific target genes (mRNAs) from multiple information sources, i.e. computationally predicted target genes of miRNAs and their respective expression profiles.<\/jats:p><jats:p>Results: We used data sets consisting of miRNA\u2013target gene binding information and expression profiles of miRNAs and mRNAs on human cancer samples. Our method allowed us to detect functionally correlated miRNA\u2013mRNA modules involved in specific biological processes from multiple data sources by using a balanced fitness function and efficient searching over multiple populations. The proposed algorithm found two miRNA\u2013mRNA modules, highly correlated with respect to their expression and biological function. Moreover, the mRNAs included in the same module showed much higher correlations when the related miRNAs were highly expressed, demonstrating our method's ability for finding coherent miRNA\u2013mRNA modules. Most members of these modules have been reported to be closely related with cancer. Consequently, our method can provide a primary source of miRNA and target sets presumed to constitute closely related parts of gene regulatory pathways.<\/jats:p><jats:p>Contact: \u00a0btzhang@bi.snu.ac.kr<\/jats:p><jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btm045","type":"journal-article","created":{"date-parts":[[2007,3,10]],"date-time":"2007-03-10T01:23:26Z","timestamp":1173489806000},"page":"1141-1147","source":"Crossref","is-referenced-by-count":125,"title":["Discovery of microRNA\u2013mRNA modules via population-based probabilistic learning"],"prefix":"10.1093","volume":"23","author":[{"given":"Je-Gun","family":"Joung","sequence":"first","affiliation":[{"name":"1 Center for Bioinformation Technology, Seoul National University, Seoul 151-742, School of Computing, Soongsil University, Seoul 156-743 and 3School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyu-Baek","family":"Hwang","sequence":"additional","affiliation":[{"name":"1 Center for Bioinformation Technology, Seoul National University, Seoul 151-742, School of Computing, Soongsil University, Seoul 156-743 and 3School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin-Wu","family":"Nam","sequence":"additional","affiliation":[{"name":"1 Center for Bioinformation Technology, Seoul National University, Seoul 151-742, School of Computing, Soongsil University, Seoul 156-743 and 3School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soo-Jin","family":"Kim","sequence":"additional","affiliation":[{"name":"1 Center for Bioinformation Technology, Seoul National University, Seoul 151-742, School of Computing, Soongsil University, Seoul 156-743 and 3School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Byoung-Tak","family":"Zhang","sequence":"additional","affiliation":[{"name":"1 Center for Bioinformation Technology, Seoul National University, Seoul 151-742, School of Computing, Soongsil University, Seoul 156-743 and 3School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea"},{"name":"1 Center for Bioinformation Technology, Seoul National University, Seoul 151-742, School of Computing, Soongsil University, Seoul 156-743 and 3School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2007,3,9]]},"reference":[{"key":"2023041209113111900_","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1182\/blood-2002-08-2482","article-title":"BCL6 gene translocation in follicular lymphoma: a harbinger of eventual transformation to diffuse aggressive lymphoma","volume":"102","author":"Akasaka","year":"2003","journal-title":"Blood"},{"key":"2023041209113111900_","article-title":"Population-Based incremental learning: a method for integrating genetic search Based function optimization and competitive learning","volume-title":"Technical Report CMU-CS-94-163","author":"Baluja","year":"1994"},{"key":"2023041209113111900_","first-page":"319","article-title":"Genetic algorithms and explicit search statistics","volume":"9","author":"Baluja","year":"1997","journal-title":"Adv. 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