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Friedman, N., Linial, M., Nachman, I. and Pe’er, D. (2000) Using Bayesian networks to analyze expression data. Journal of Computational Biology, 7, 601-620. doi:10.1089/106652700750050961

has been cited by the following article:

• TITLE: Modeling of gene regulatory networks: A review

  AUTHORS: Nedumparambathmarath Vijesh, Swarup Kumar Chakrabarti, Janardanan Sreekumar

  KEYWORDS: Gene Network; Gene Expression Data; Gene Regulation

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.6 No.2A, February 27, 2013

  ABSTRACT: Gene regulatory networks play an important role the molecular mechanism underlying biological processes. Modeling of these networks is an important challenge to be addressed in the post genomic era. Several methods have been proposed for estimating gene networks from gene expression data. Computational methods for development of network models and analysis of their functionality have proved to be valuable tools in bioinformatics applications. In this paper we tried to review the different methods for reconstructing gene regulatory networks.