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Evolution of extrema features reveals optimal stimuli for biological state transitions.

ABSTRACT: The ability to define the unique features of an input stimulus needed to control switch-like behavior in biological systems is an important problem in computational biology and medicine. We show in this study how highly complex and intractable optimization problems can be simplified by restricting the search to the signal's extrema as key feature points, and evolving the extrema features towards optimal solutions that closely match solutions derived from gradient-based methods. Our results suggest a model-independent approach for solving a class of optimization problems related to controlling switch-like state transitions.

SUBMITTER: Chang J

PROVIDER: S-EPMC5821862 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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Evolution of extrema features reveals optimal stimuli for biological state transitions.

Chang Joshua J Chang Joshua J Paydarfar David D

Scientific reports 20180221 1

The ability to define the unique features of an input stimulus needed to control switch-like behavior in biological systems is an important problem in computational biology and medicine. We show in this study how highly complex and intractable optimization problems can be simplified by restricting the search to the signal's extrema as key feature points, and evolving the extrema features towards optimal solutions that closely match solutions derived from gradient-based methods. Our results sugge ...[more]

PMID: 29467377

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