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Updated: Jul 7, 2026

The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions
Published on: February 16, 2017
Emergent decision-making in biological signal transduction networks
Tomás Helikar1, John Konvalina, Jack Heidel
1Department of Pathology and Microbiology, University of Nebraska Medical Center, 983135 Nebraska Medical Center, Omaha, NE 68198, USA.
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.
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