This paper provides a brief introduction to learning Bayesian networks from gene-expression data. The method is contrasted with other approaches to the reverse engineering of biochemical networks, and the Bayesian learning paradigm is briefly described. The article demonstrates an application to a simple synthetic toy problem and evaluates the inference performance in terms of ROC (receiver operator characteristic) curves.
Conference Article| December 01 2003
Reverse engineering of genetic networks with Bayesian networks
Biochem Soc Trans (2003) 31 (6): 1516–1518.
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D. Husmeier; Reverse engineering of genetic networks with Bayesian networks. Biochem Soc Trans 1 December 2003; 31 (6): 1516–1518. doi: https://doi.org/10.1042/bst0311516
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