{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T06:16:59Z","timestamp":1768285019902,"version":"3.49.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"21","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Biclustering has been emerged as a powerful tool for identification of a group of co-expressed genes under a subset of experimental conditions (measurements) present in a gene expression dataset. Several biclustering algorithms have been proposed till date. In this article, we address some of the important shortcomings of these existing biclustering algorithms and propose a new correlation-based biclustering algorithm called bi-correlation clustering algorithm (BCCA).<\/jats:p>\n               <jats:p>Results: BCCA has been able to produce a diverse set of biclusters of co-regulated genes over a subset of samples where all the genes in a bicluster have a similar change of expression pattern over the subset of samples. Moreover, the genes in a bicluster have common transcription factor binding sites in the corresponding promoter sequences. The presence of common transcription factors binding sites, in the corresponding promoter sequences, is an evidence that a group of genes in a bicluster are co-regulated. Biclusters determined by BCCA also show highly enriched functional categories. Using different gene expression datasets, we demonstrate strength and superiority of BCCA over some existing biclustering algorithms.<\/jats:p>\n               <jats:p>Availability: The software for BCCA has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http:\/\/www.isical.ac.in\/\u223crajat. Then it needs to be installed. Two word files (included in the zip file) need to be consulted before installation and execution of the software.<\/jats:p>\n               <jats:p>Contact: \u00a0rajat@isical.ac.in<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp526","type":"journal-article","created":{"date-parts":[[2009,9,5]],"date-time":"2009-09-05T00:14:25Z","timestamp":1252109665000},"page":"2795-2801","source":"Crossref","is-referenced-by-count":34,"title":["Bi-correlation clustering algorithm for determining a set of co-regulated genes"],"prefix":"10.1093","volume":"25","author":[{"given":"Anindya","family":"Bhattacharya","sequence":"first","affiliation":[{"name":"1 Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata 700152 and 2 Machine Intelligence Unit, Indian Statistical Institute, Kolkata 700108, West Bengal, India"}]},{"given":"Rajat K.","family":"De","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata 700152 and 2 Machine Intelligence Unit, Indian Statistical Institute, Kolkata 700108, West Bengal, India"}]}],"member":"286","published-online":{"date-parts":[[2009,9,3]]},"reference":[{"key":"2023013112172400600_B1","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1093\/nar\/gki354","article-title":"Toucan 2: the all-inclusive open source workbench for regulatory sequence analysis","volume":"33","author":"Aerts","year":"2005","journal-title":"Nucleic Acid Res."},{"key":"2023013112172400600_B2","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/1471-2105-5-18","article-title":"Quantifying the relationship between co-expression, co-regulation and gene function","volume":"5","author":"Allocco","year":"2004","journal-title":"BMC Bioinformatics"},{"key":"2023013112172400600_B3","first-page":"49","article-title":"Discovering local structure in gene expression data: the order-preserving submatrix problem","volume-title":"Proceedings of the Sixth International Conference on Computational Biology (RECOMB 02)","author":"Ben-Dor","year":"2002"},{"key":"2023013112172400600_B4","doi-asserted-by":"crossref","first-page":"031902","DOI":"10.1103\/PhysRevE.67.031902","article-title":"Iterative signature algorithm for the analysis of large-scale gene expression data","volume":"67","author":"Bergmann","year":"2003","journal-title":"Phys. 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