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

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

2003-11-13

arxiv.org/abs/q-bio/0311017v2

Bioinformatics 21, 1172 (2005).

Biology

Quantitative Biology

Quantitative Methods

7 pages, 6 figures in main text; 2 text pages, 7 figures, 1 table in supplement; rewritten version

Scientific paper

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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