Document Type

Article

Publication Date

2-1-2008

Publication Title

PNAS

Volume

105

Issue

6

First Page

1913

Last Page

1918

Abstract

The complexity of biochemical intracellular signal transduction networks has led to speculation that the high degree of interconnectivity that exists in these networks transforms them into an information processing network. To test this hypothesis directly, a large scale model was created with the logical mechanism of each node described completely to allow simulation and dynamical analysis. Exposing the network to tens of thousands of random combinations of inputs and analyzing the combined dynamics of multiple outputs revealed a robust system capable of clustering widely varying input combinations into equivalence classes of biologically relevant cellular responses. This capability was nontrivial in that the network performed sharp, nonfuzzy classifications even in the face of added noise, a hallmark of real-world decision-making.

Comments

This article contains supporting information online at www.pnas.org/cgi/content/full/0705088105/DC1. © 2008 by The National Academy of Sciences of the USA

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