Finding regulatory modules through large-scale gene-expression data analysis

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dc.creatorKloster, Morten
dc.creatorTang, Chao
dc.creatorWingreen, Ned
dc.date2003-11-13
dc.date2004-01-19
dc.date.accessioned2026-07-07T06:31:14Z
dc.date.available2026-07-07T06:31:14Z
dc.descriptionThe use of gene microchips has enabled a rapid accumulation of gene-expression data. One of the major challenges of analyzing this data is the diversity, in both size and signal strength, of the various modules in the gene regulatory networks of organisms. Based on the Iterative Signature Algorithm [Bergmann, S., Ihmels, J. and Barkai, N. (2002) Phys. Rev. E 67, 031902], we present an algorithm - the Progressive Iterative Signature Algorithm (PISA) - that, by sequentially eliminating modules, allows unsupervised identification of both large and small regulatory modules. We applied PISA to a large set of yeast gene-expression data, and, using the Gene Ontology annotation database as a reference, found that our algorithm is much better able to identify regulatory modules than methods based on high-throughput transcription-factor binding experiments or on comparative genomics.
dc.description7 pages, 6 figures in main text; 2 text pages, 7 figures, 1 table in supplement; rewritten version
dc.identifierhttps://arxiv.org/abs/q-bio/0311017
dc.identifierhttp://arxiv.org/abs/q-bio/0311017
dc.identifierBioinformatics 21, 1172 (2005).
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/98549
dc.subjectQuantitative Methods
dc.subjectGenomics
dc.titleFinding regulatory modules through large-scale gene-expression data analysis
dc.typetext

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