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Computational approaches to the integration of gene expression, ChIP-chip and sequence data in the inference of gene regulatory networks

By Emma J. Cooke, Richard S. Savage and David L. Wild

Abstract

A major challenge in systems biology is the ability to model complex regulatory interactions, such as gene regulatory networks, and a number of computational approaches have been developed over recent years to address this challenge. This paper reviews a number of these approaches, with a focus on probabilistic graphical models and the integration of diverse data sets, such as gene expression and transcription factor binding site location and activity. (C) 2009 Elsevier Ltd. All rights reserved

Topics: QH301
Publisher: Elsevier Science Ltd. / Academic Press Ltd.
Year: 2009
DOI identifier: 10.1016/j.semcdb.2009.08.004
OAI identifier: oai:wrap.warwick.ac.uk:17146
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