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Other

Description:

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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      Keywords:

      NSDL,computational biology,NSDL_SetSpec_BEN,signal transduction,General,methodology,oai:nsdl.org:2200/20080618224242993T,Life Science,modeling,Computing and Information

      Language:

      English

      Access Privileges:

      Public - Available to anyone

      License Deed:

      Creative Commons Attribution Non-Commercial Share Alike

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