Modeling Signaling Networks

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Science's STKE  26 Apr 2005:
Vol. 2005, Issue 281, pp. tw157
DOI: 10.1126/stke.2812005tw157

The prediction of causal influences between components of a signaling network requires detailed modeling from large data sets. Single-cell measurements of the phosphorylation state of a panel of signaling proteins with phosphospecific antibodies after various treatments that influenced cellular signaling provided sufficient data so that Sachs et al. (see the Perspective by Brent and Lok) could apply a Bayesian network inference algorithm to map a signaling network and infer causal influences between the components of the network. Known connections were reproduced, and a newly discovered connection was experimentally tested and found indeed to be of biological relevance.

K. Sachs, O. Perez, D. Pe'er, D. A. Lauffenburger, G. P. Nolan, Causal protein-signaling networks derived from multiparameter single-cell data. Science 308, 523-529 (2005). [Abstract] [Full Text]

R. Brent, L. Lok, A fishing buddy for hypothesis generators. Science 308, 504-506 (2005). [Summary] [Full Text]

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