Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.
Nucleic Acids Res, 2012/3;40(6):2377-98.
Hurley D[1], Araki H, Tamada Y, Dunmore B, Sanders D, Humphreys S, Affara M, Imoto S, Yasuda K, Tomiyasu Y, Tashiro K, Savoie C, Cho V, Smith S, Kuhara S, Miyano S, Charnock-Jones DS, Crampin EJ, Print CG
Affiliations
PMID: 22121215DOI: 10.1093/nar/gkr902
Impact factor: 19.16
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.
MeSH terms
Cells, Cultured; Computer Graphics; Gene Expression Profiling; Gene Regulatory Networks; Human Umbilical Vein Endothelial Cells; Humans; NF-kappa B; NF-kappa B p50 Subunit; Oligonucleotide Array Sequence Analysis; RNA, Small Interfering; Software; Tumor Necrosis Factor-alpha
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