dc.contributor.author	Pati, Amrita	en
dc.contributor.author	Vasquez-Robinet, Cecilia	en
dc.contributor.author	Heath, Lenwood S.	en
dc.contributor.author	Grene, Ruth	en
dc.contributor.author	Murali, T. M.	en
dc.contributor.department	Computer Science	en
dc.contributor.department	School of Plant and Environmental Sciences	en
dc.date.accessioned	2012-08-24T12:17:24Z	en
dc.date.available	2012-08-24T12:17:24Z	en
dc.date.issued	2006-04-21	en
dc.date.updated	2012-08-24T12:17:24Z	en
dc.description.abstract	Background Modeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions. Methods XcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution), and on the new sum of absolute values statistic (SAV) that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion. Results XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at https://bioinformatics.cs.vt.edu/xcisclique/.	en
dc.description.version	Published version	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	BMC Bioinformatics. 2006 Apr 21;7(1):218	en
dc.identifier.doi	https://doi.org/10.1186/1471-2105-7-218	en
dc.identifier.uri	http://hdl.handle.net/10919/18951	en
dc.language.iso	en	en
dc.rights	Creative Commons Attribution 4.0 International	en
dc.rights.holder	Amrita Pati et al.; licensee BioMed Central Ltd.	en
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	en
dc.title	XcisClique: analysis of regulatory bicliques	en
dc.title.serial	BMC Bioinformatics	en
dc.type	Article - Refereed	en
dc.type.dcmitype	Text	en

XcisClique: analysis of regulatory bicliques

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