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Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.

ABSTRACT: Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.

SUBMITTER: Hurley D

PROVIDER: S-EPMC3315333 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.

Hurley Daniel D Araki Hiromitsu H Tamada Yoshinori Y Dunmore Ben B Sanders Deborah D Humphreys Sally S Affara Muna M Imoto Seiya S Yasuda Kaori K Tomiyasu Yuki Y Tashiro Kosuke K Savoie Christopher C Cho Vicky V Smith Stephen S Kuhara Satoru S Miyano Satoru S Charnock-Jones D Stephen DS Crampin Edmund J EJ Print Cristin G CG

Nucleic acids research 20111124 6

Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from ...[more]

PMID: 22121215

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