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Issue 3, 2012
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A framework for designing and analyzing binary decision-making strategies in cellular systems

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Abstract

Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway.

Graphical abstract: A framework for designing and analyzing binary decision-making strategies in cellular systems

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Publication details

The article was received on 21 Sep 2011, accepted on 05 Feb 2012 and first published on 27 Feb 2012


Article type: Paper
DOI: 10.1039/C2IB00114D
Citation: Integr. Biol., 2012,4, 310-317
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    A framework for designing and analyzing binary decision-making strategies in cellular systems

    J. R. Porter, B. W. Andrews and P. A. Iglesias, Integr. Biol., 2012, 4, 310
    DOI: 10.1039/C2IB00114D

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