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Be cause genes may be co-regulated only across a subset of all observed experimental conditions, <jats:italic>biclustering<\/jats:italic> (clustering of genes <jats:italic>and<\/jats:italic> conditions) is more appropriate than standard clustering. Co-regulated genes are also often functionally (physically, spatially, genetically, and\/or evolutionarily) associated, and such <jats:italic>a priori<\/jats:italic> known or pre-computed associations can provide support for appropriately grouping genes. One important association is the presence of one or more common cis-regulatory motifs. In organisms where these motifs are not known, their <jats:italic>de novo<\/jats:italic> detection, integrated into the clustering algorithm, can help to guide the process towards more biologically parsimonious solutions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We have developed an algorithm, cMonkey, that detects putative co-regulated gene groupings by integrating the biclustering of gene expression data and various functional associations with the <jats:italic>de novo<\/jats:italic> detection of sequence motifs.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>We have applied this procedure to the archaeon <jats:italic>Halobacterium<\/jats:italic> NRC-1, as part of our efforts to decipher its regulatory network. In addition, we used cMonkey on public data for three organisms in the other two domains of life: <jats:italic>Helicobacter pylori, Saccharomyces cerevisiae<\/jats:italic>, and <jats:italic>Escherichia coli<\/jats:italic>. The biclusters detected by cMonkey both recapitulated known biology and enabled novel predictions (some for <jats:italic>Halobacterium<\/jats:italic> were subsequently confirmed in the laboratory). For example, it identified the <jats:italic>bacteriorhodopsin<\/jats:italic> regulon, assigned additional genes to this regulon with apparently unrelated function, and detected its known promoter motif. We have performed a thorough comparison of cMonkey results against other clustering methods, and find that cMonkey biclusters are more parsimonious with all available evidence for co-regulation.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-7-280","type":"journal-article","created":{"date-parts":[[2006,6,3]],"date-time":"2006-06-03T07:40:13Z","timestamp":1149320413000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":206,"title":["Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks"],"prefix":"10.1186","volume":"7","author":[{"given":"David J","family":"Reiss","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nitin S","family":"Baliga","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Bonneau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2006,6,2]]},"reference":[{"key":"1019_CR1","unstructured":"European bioinformatics institute gene ontology annotations[http:\/\/www.ebi.ac.uk\/GOA\/proteomes.html]"},{"key":"1019_CR2","unstructured":"Kegg genomes web site[ftp:\/\/ftp.genome.ad.jp\/pub\/kegg\/genomes\/]"},{"key":"1019_CR3","unstructured":"Stanford microarray database[http:\/\/genome-www5.stanford.edu]"},{"key":"1019_CR4","unstructured":"CMONKEY web site[http:\/\/halo.systemsbiology.net\/cmonkey]"},{"key":"1019_CR5","unstructured":"The R project for statistical computing[http:\/\/www.r-project.org]"},{"key":"1019_CR6","volume-title":"Bioinformatics","author":"A Prelic","year":"2006","unstructured":"Prelic A, Bleuler S, Zimmermann P, Wille A, Buhlmann P, Gruissem W, Hennig L, Thiele L, Zitzler E: A systematic comparison and evaluation of biclustering methods for gene expression data. 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