Evolution of extrema features reveals optimal stimuli for biological state transitions

Scientific Reports
Joshua Chang, David Paydarfar

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.

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Citations

Aug 14, 2018·Biological cybernetics·Joshua Chang, David Paydarfar
Jul 10, 2021·Chaos·Jacques BélairJohn G Milton

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Methods Mentioned

BETA
feature extraction
chips

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