Quantifying evolvability in small biological networks

Dept. of Phys., Columbia Univ., New York, NY, USA
IET Systems Biology (Impact Factor: 1.67). 10/2009; DOI: 10.1049/iet-syb.2008.0165
Source: IEEE Xplore

ABSTRACT The authors introduce a quantitative measure of the capacity of a small biological network to evolve. The measure is applied to a stochastic description of the experimental setup of Guet et al. ( Science 2002, 296, pp. 1466), treating chemical inducers as functional inputs to biochemical networks and the expression of a reporter gene as the functional output. The authors take an information-theoretic approach, allowing the system to set parameters that optimise signal processing ability, thus enumerating each network's highest-fidelity functions. All networks studied are highly evolvable by the measure, meaning that change in function has little dependence on change in parameters. Moreover, each network's functions are connected by paths in the parameter space along which information is not significantly lowered, meaning a network may continuously change its functionality without completely losing it along the way. This property further underscores the evolvability of the networks.


Available from: Ilya Nemenman, Jun 16, 2015
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