Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles.

Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Research Abstract Details 

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Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Abstract Text:

Jeremiah J Faith,Boris Hayete,Joshua T Thaden,Ilaria Mogno,Jamey Wierzbowski,Guillaume Cottarel,Simon Kasif,James J Collins,Timothy S Gardner,

Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data.

Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Publishing Authors By Initials

JJ Faith,B Hayete,JT Thaden,I Mogno,J Wierzbowski,G Cottarel,S Kasif,JJ Collins,TS Gardner,

For similar genetic processes: gene expression: transcription, genetic research abstracts see: genetic processes: gene expression: transcription, genetic research

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Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: PLoS biology

VOLUME: 5

Page Numbers: e8

Journal Abbreviation:

ISSN: 1545-7885

DAY: 3

MONTH: Jan

YEAR: 2007

Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Information

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LANGUAGE: eng

NlmUniqueID: 101183755

Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Keywords Mesh Terms:

KEYWORDS: Transcription, Genetic

MESH TERMS: genetics

Chemical & Substance for Abstract: Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. Information

Substance Name: Iron

Registry Number: 7439-89-6

Grant and Affiliation Information for Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles.

AFFILIATION: Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.

Country: United States

AGENCY: United States PHS

GRANT: HHSN268200248178C

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MEDLINETA: PLoS Biol

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