dorsal/arxiv
View SchemaFinding regulatory modules through large-scale gene-expression data analysis
| Authors | Morten Kloster, Chao Tang, Ned Wingreen |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0311017 |
| URL | https://arxiv.org/abs/q-bio/0311017 |
| Journal | Bioinformatics 21, 1172 (2005). |
Abstract
The 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.
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"abstract": "The use of gene microchips has enabled a rapid accumulation of\ngene-expression data. One of the major challenges of analyzing this data is the\ndiversity, in both size and signal strength, of the various modules in the gene\nregulatory networks of organisms. Based on the Iterative Signature Algorithm\n[Bergmann, S., Ihmels, J. and Barkai, N. (2002) Phys. Rev. E 67, 031902], we\npresent an algorithm - the Progressive Iterative Signature Algorithm (PISA) -\nthat, by sequentially eliminating modules, allows unsupervised identification\nof both large and small regulatory modules. We applied PISA to a large set of\nyeast gene-expression data, and, using the Gene Ontology annotation database as\na reference, found that our algorithm is much better able to identify\nregulatory modules than methods based on high-throughput transcription-factor\nbinding experiments or on comparative genomics.",
"arxiv_id": "q-bio/0311017",
"authors": [
"Morten Kloster",
"Chao Tang",
"Ned Wingreen"
],
"categories": [
"q-bio.QM",
"q-bio.GN"
],
"journal_ref": "Bioinformatics 21, 1172 (2005).",
"title": "Finding regulatory modules through large-scale gene-expression data analysis",
"url": "https://arxiv.org/abs/q-bio/0311017"
},
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