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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.

SUBMITTER: Porter JR

PROVIDER: S-EPMC4547352 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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A framework for designing and analyzing binary decision-making strategies in cellular systems.

Porter Joshua R JR Andrews Burton W BW Iglesias Pablo A PA

Integrative biology : quantitative biosciences from nano to macro 20120301 3

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 ...[more]

PMID: 22370552

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Project description:The crucial role of sustainable development and resiliency strategies is undeniable in today’s competitive market space, especially after the Coronavirus outbreak. Hence, this research develops a multistage decision-making framework to investigate the supply chain network design problem considering the sustainability and resiliency dimensions. In this way, the scores of the potential suppliers based on the sustainability and resilience dimensions were calculated using the MADM methods, and then, these scores were applied as inputs in the proposed mathematical model (the second stage), which determined which supplier should be selected. The proposed model aims to minimize the total costs, maximize the suppliers' sustainability and resiliency, and maximize the distribution centers' resiliency. Then, the proposed model is solved by the preemptive fuzzy goal programming method. Overall, the main objectives and aims of the current work are to present a comprehensive decision-making model that can incorporate the sustainability and resilience dimensions into the supplier selection and supply chain configuration processes. In general, the main contributions and advantages of this work can be summarized as follows: (i) this research simultaneously investigates the sustainability and resiliency concepts in the dairy supply chain, (ii) the current work develops an efficient multistage decision-making model that can evaluate the suppliers based on the resilience and sustainability dimensions and configure the supply chain network, simultaneously. Based on the obtained results, the responsiveness and facilities reinforcement indicators are the most important indicators for the resilient aspect. On the other hand, reliability and quality are the most important indicators of sustainability aspect. Also, the results show that a large percentage of supply chain costs are related to purchasing and production costs. Besides, according to the outputs, the total cost of supply chain increases by enhancing the demand. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s10098-023-02538-8.

Dataset Information

A framework for designing and analyzing binary decision-making strategies in cellular systems.

Publications

A framework for designing and analyzing binary decision-making strategies in cellular systems.

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