A Primer on Learning in Bayesian Networks for Computational Biology

Abstract

Bayesian networks (BNs) provide a neat and compact representation for expressing joint probability distributions (JPDs) and for inference. They are becoming increasingly important in the biological sciences for the tasks of inferring cellular networks [1], modelling protein signalling pathways [2], systems biology, data integration [3], classification [4… (More)
DOI: 10.1371/journal.pcbi.0030129

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Cite this paper

@article{Needham2007APO, title={A Primer on Learning in Bayesian Networks for Computational Biology}, author={Chris J. Needham and James R. Bradford and Andrew J. Bulpitt and David R. Westhead}, journal={PLoS Computational Biology}, year={2007}, volume={3}, pages={799 - 805} }