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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.
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PRESENTATIONS
Illés J. Farkas, Tamás Korcsmáros, István A. Kovács, Ágoston Mihalik, Robin Palotai, Gábor I. Simkó, Kristóf Z. Szalay, Máté Szalay-Beko, Tibor Vellai, Shijun Wang, and Peter Csermely (17 May 2011) Sci. Signal.4 (173), pt3.
[DOI: 10.1126/scisignal.2001950] |Abstract »|Full Text »|PDF »|Slideshow »
EDITORS' CHOICE
Nancy R. Gough (8 May 2007) Sci. STKE2007 (385), tw156.
[DOI: 10.1126/stke.3852007tw156] |Abstract »
L. Bryan Ray, Elizabeth M. Adler, Nancy R. Gough, and Lisa D. Chong (10 February 2004) Sci. STKE2004 (219), eg3.
[DOI: 10.1126/stke.2192004eg3] |Abstract »|Full Text »|PDF »
Network Modeling Reveals Steps in Angiotensin Peptide Processing.
J. H. Schwacke, J. C. G. Spainhour, J. L. Ierardi, J. M. Chaves, J. M. Arthur, M. G. Janech, and J. C. Q. Velez (2013)
Hypertension
61, 690-700
|Abstract »|Full Text »|PDF »
Integrating literature-constrained and data-driven inference of signalling networks.
F. Eduati, J. De Las Rivas, B. Di Camillo, G. Toffolo, and J. Saez-Rodriguez (2012)
Bioinformatics
28, 2311-2317
|Abstract »|Full Text »|PDF »
Computational Approaches for Analyzing Information Flow in Biological Networks.