Biochemistry, Department of
Date of this Version
2-12-2008
Citation
PNAS (February 12, 2008) vol. 105, no. 6, pp. 1913-1918.
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.
Included in
Biochemistry Commons, Biotechnology Commons, Other Biochemistry, Biophysics, and Structural Biology Commons
Comments
Copyright © 2008 by The National Academy of Sciences of the USA. Used by permission.