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L _p -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.

ABSTRACT: The design of systems or models that work robustly under uncertainty and environmental fluctuations is a key challenge in both engineering and science. This is formalized in the design-centering problem, which is defined as finding a design that fulfills given specifications and has a high probability of still doing so if the system parameters or the specifications fluctuate randomly. Design centering is often accompanied by the problem of quantifying the robustness of a system. Here we present a novel adaptive statistical method to simultaneously address both problems. Our method, L _p -Adaptation, is inspired by the evolution of robustness in biological systems and by randomized schemes for convex volume computation. It is able to address both problems in the general, non-convex case and at low computational cost. We describe the concept and the algorithm, test it on known benchmarks, and demonstrate its real-world applicability in electronic and biological systems. In all cases, the present method outperforms the previous state of the art. This enables re-formulating optimization problems in engineering and biology as design centering problems, taking global system robustness into account.

SUBMITTER: Asmus J

PROVIDER: S-EPMC5532288 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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L <sub>p</sub> -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.

Asmus Josefine J Müller Christian L CL Sbalzarini Ivo F IF

Scientific reports 20170727 1

The design of systems or models that work robustly under uncertainty and environmental fluctuations is a key challenge in both engineering and science. This is formalized in the design-centering problem, which is defined as finding a design that fulfills given specifications and has a high probability of still doing so if the system parameters or the specifications fluctuate randomly. Design centering is often accompanied by the problem of quantifying the robustness of a system. Here we present ...[more]

PMID: 28751662

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Project description:A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a general basis for how biological systems function dynamically.

Dataset Information

L _p -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.

Publications

L <sub>p</sub> -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.

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Dataset Information

L p -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.

Publications

L <sub>p</sub> -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

L _p -Adaptation: Simultaneous Design Centering and Robustness Estimation of Electronic and Biological Systems.