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.
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机译：动机：基因芯片的使用可以快速积累基因表达数据。分析此数据的主要挑战之一是生物基因调控网络中各个模块的大小和信号强度的多样性。结果：基于迭代签名算法还有北卡罗来纳州的巴尔凯（2002）物理学。 Rev. E 67，031902]，我们提出了一种算法-渐进式迭代签名算法（PISA），该算法通过顺序消除模块，可以无监督地识别大型和小型监管模块。我们将PISA应用于大量酵母基因表达数据，并以Gene Ontology数据库为参考，发现该算法比基于高通量转录因子结合实验或比较基因组学。
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