  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.
