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Gene network inference and visualization tools for biologists: application to new human transcriptome datasets
Authors:Hurley Daniel  Araki Hiromitsu  Tamada Yoshinori  Dunmore Ben  Sanders Deborah  Humphreys Sally  Affara Muna  Imoto Seiya  Yasuda Kaori  Tomiyasu Yuki  Tashiro Kosuke  Savoie Christopher  Cho Vicky  Smith Stephen  Kuhara Satoru  Miyano Satoru  Charnock-Jones D Stephen  Crampin Edmund J  Print Cristin G
Affiliation:Auckland Bioengineering Institute, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.
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.
Keywords:
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