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Sci. STKE, 26 April 2005
Vol. 2005, Issue 281, p. pl4
[DOI: 10.1126/stke.2812005pl4]

PROTOCOLS

Bayesian Network Analysis of Signaling Networks: A Primer

Dana Pe'er*

Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.

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.

Corresponding author. E-mail: dpeer{at}genetics.med.harvard.edu

Citation: D. Pe'er, Bayesian Network Analysis of Signaling Networks: A Primer. Sci. STKE 2005, pl4 (2005).

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THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data.
K. Sachs, O. Perez, D. Pe'er, D. A. Lauffenburger, and G. P. Nolan (2005)
Science 308, 523-529
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