Reference: Scott MS, et al. (2005) Identifying regulatory subnetworks for a set of genes. Mol Cell Proteomics 4(5):683-92

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Abstract


High throughput genomic/proteomic strategies, such as microarray studies, drug screens, and genetic screens, often produce a list of genes that are believed to be important for one or more reasons. Unfortunately it is often difficult to discern meaningful biological relationships from such lists. This study presents a new bioinformatic approach that can be used to identify regulatory subnetworks for lists of significant genes or proteins. We demonstrate the utility of this approach using an interaction network for yeast constructed from BIND, TRANSFAC, SCPD, and chromatin immunoprecipitation (ChIP)-Chip data bases and lists of genes from well known metabolic pathways or differential expression experiments. The approach accurately rediscovers known regulatory elements of the heat shock response as well as the gluconeogenesis, galactose, glycolysis, and glucose fermentation pathways in yeast. We also find evidence supporting a previous conjecture that approximately half of the enzymes in a metabolic pathway are transcriptionally co-regulated. Finally we demonstrate a previously unknown connection between GAL80 and the diauxic shift in yeast.

Reference Type
Comparative Study | Journal Article | Research Support, Non-U.S. Gov't
Authors
Scott MS, Perkins T, Bunnell S, Pepin F, Thomas DY, Hallett M
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Gene Ontology Annotations


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Gene/Complex Qualifier Gene Ontology Term Aspect Annotation Extension Evidence Method Source Assigned On Reference

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Gene Phenotype Experiment Type Mutant Information Strain Background Chemical Details Reference

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Gene Disease Ontology Term Qualifier Evidence Method Source Assigned On Reference

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Interactor Interactor Allele Assay Annotation Action Phenotype SGA score P-value Source Reference

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Interactor Interactor Assay Annotation Action Modification Source Reference

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Gene Species Gene ID Strain background Direction Details Source Reference