Bayesian network analysis of signaling networks: a primer.

Authors: Pe'er D

Abstract: High-throughput proteomic data can be used to reveal the connectivity of signaling networks and the influences between signaling molecules. We present a primer on the use of Bayesian networks for this task. Bayesian networks have been successfully used to derive causal influences among biological signaling molecules (for example, in the analysis of intracellular multicolor flow cytometry). We discuss ways to automatically derive a Bayesian network model from proteomic data and to interpret the resulting model.

Keywords: Algorithms; Animals; *Bayes Theorem; Causality; Genotype; Humans; Likelihood Functions; Markov Chains; Models, Biological; *Proteomics; *Signal Transduction
Journal: Science's STKE : signal transduction knowledge environment
Volume: 2005
Issue: 281
Pages: pl4
Date: April 28, 2005
PMID: 15855409
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Citation:

Pe'er D (2005) Bayesian network analysis of signaling networks: a primer. Science's STKE : signal transduction knowledge environment 2005: pl4.



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