title: A framework for designing and analyzing binary decision-making strategies in cellular systems.
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.
authors.affiliation: Department of Electrical and Computer Engineering, The Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA.
authors.forename: Joshua R
authors.initials: JR
authors.lastname: Porter
authors.forename: Burton W
authors.initials: BW
authors.lastname: Andrews
authors.forename: Pablo A
authors.initials: PA
authors.lastname: Iglesias
mesh_terms: D017209:Apoptosis / Q000502:physiology; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D003657:Decision Making; D003661:Decision Support Techniques; D007257:Information Theory; D008954:Models, Biological; D013269:Stochastic Processes; D049490:Systems Biology