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

M. Kloster, C. Tang, N. S. Wingreen

Research output: Contribution to journalArticle

27 Scopus citations

Abstract

Motivation: 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. Results: 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 database as a reference, found that the algorithm is much better able to identify regulatory modules than methods based on high-throughput transcription-factor binding experiments or on comparative genomics.

Original languageEnglish (US)
Pages (from-to)1172-1179
Number of pages8
JournalBioinformatics
Volume21
Issue number7
DOIs
StatePublished - Apr 1 2005

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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