{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T10:42:41Z","timestamp":1742380961248},"reference-count":2,"publisher":"Oxford University Press (OUP)","issue":"20","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Clustering methods including k-means, SOM, UPGMA, DAA, CLICK, GENECLUSTER, CAST, DHC, PMETIS and KMETIS have been widely used in biological studies for gene expression, protein localization, sequence recognition and more. All these clustering methods have some benefits and drawbacks. We propose a novel graph-based clustering software called COMUSA for combining the benefits of a collection of clusterings into a final clustering having better overall quality.<\/jats:p>\n               <jats:p>Results: COMUSA implementation is compared with PMETIS, KMETIS and k-means. Experimental results on artificial, real and biological datasets demonstrate the effectiveness of our method. COMUSA produces very good quality clusters in a short amount of time.<\/jats:p>\n               <jats:p>Availability: \u00a0http:\/\/www.cs.umb.edu\/\u223csmimarog\/comusa<\/jats:p>\n               <jats:p>Contact: \u00a0selim.mimaroglu@bahcesehir.edu.tr<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq489","type":"journal-article","created":{"date-parts":[[2010,8,25]],"date-time":"2010-08-25T01:53:25Z","timestamp":1282701205000},"page":"2645-2646","source":"Crossref","is-referenced-by-count":9,"title":["Obtaining better quality final clustering by merging a collection of clusterings"],"prefix":"10.1093","volume":"26","author":[{"given":"Selim","family":"Mimaroglu","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Bahcesehir University, Ciragan Caddesi 34353 Besiktas, Istanbul, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ertunc","family":"Erdil","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Bahcesehir University, Ciragan Caddesi 34353 Besiktas, Istanbul, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,8,24]]},"reference":[{"key":"2023012507564007100_B1","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/BF01908075","article-title":"Comparing partitions","volume":"2","author":"Hubert","year":"1985","journal-title":"J. Classif."},{"key":"2023012507564007100_B2","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","article-title":"Data clustering: 50 years beyond k-means","volume":"31","author":"Jain","year":"2010","journal-title":"Pattern Recogni. Lett."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/20\/2645\/48853343\/bioinformatics_26_20_2645.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/20\/2645\/48853343\/bioinformatics_26_20_2645.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T07:57:11Z","timestamp":1674633431000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/26\/20\/2645\/195064"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,8,24]]},"references-count":2,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2010,10,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btq489","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2010,10,15]]},"published":{"date-parts":[[2010,8,24]]}}}