Principles of Adaptive Sorting Revealed by In Silico Evolution

Jean-Benoît Lalanne and Paul François
Phys. Rev. Lett. 110, 218102 – Published 21 May 2013
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Abstract

Many biological networks have to filter out useful information from a vast excess of spurious interactions. In this Letter, we use computational evolution to predict design features of networks processing ligand categorization. The important problem of early immune response is considered as a case study. Rounds of evolution with different constraints uncover elaborations of the same network motif we name “adaptive sorting.” Corresponding network substructures can be identified in current models of immune recognition. Our work draws a deep analogy between immune recognition and biochemical adaptation.

  • Received 8 February 2013

DOI:https://doi.org/10.1103/PhysRevLett.110.218102

© 2013 American Physical Society

Authors & Affiliations

Jean-Benoît Lalanne and Paul François

  • Physics Department, McGill University, Montreal, Quebec, Canada H3A 2T8

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Issue

Vol. 110, Iss. 21 — 24 May 2013

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