Computing with Competition in Biochemical Networks

Anthony J. Genot, Teruo Fujii, and Yannick Rondelez
Phys. Rev. Lett. 109, 208102 – Published 13 November 2012
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Abstract

Cells rely on limited resources such as enzymes or transcription factors to process signals and make decisions. However, independent cellular pathways often compete for a common molecular resource. Competition is difficult to analyze because of its nonlinear global nature, and its role remains unclear. Here we show how decision pathways such as transcription networks may exploit competition to process information. Competition for one resource leads to the recognition of convex sets of patterns, whereas competition for several resources (overlapping or cascaded regulons) allows even more general pattern recognition. Competition also generates surprising couplings, such as correlating species that share no resource but a common competitor. The mechanism we propose relies on three primitives that are ubiquitous in cells: multiinput motifs, competition for a resource, and positive feedback loops.

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  • Received 20 May 2012

DOI:https://doi.org/10.1103/PhysRevLett.109.208102

© 2012 American Physical Society

Authors & Affiliations

Anthony J. Genot, Teruo Fujii, and Yannick Rondelez*

  • LIMMS/CNRS-IIS, Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan

  • *rondelez@iis.u-tokyo.ac.jp

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Issue

Vol. 109, Iss. 20 — 16 November 2012

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