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Design Principles of Biological Oscillators through Optimization: Forward and Reverse Analysis

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  • Irene Otero-Muras
  • Julio R Banga

Abstract

From cyanobacteria to human, sustained oscillations coordinate important biological functions. Although much has been learned concerning the sophisticated molecular mechanisms underlying biological oscillators, design principles linking structure and functional behavior are not yet fully understood. Here we explore design principles of biological oscillators from a multiobjective optimization perspective, taking into account the trade-offs between conflicting performance goals or demands. We develop a comprehensive tool for automated design of oscillators, based on multicriteria global optimization that allows two modes: (i) the automatic design (forward problem) and (ii) the inference of design principles (reverse analysis problem). From the perspective of synthetic biology, the forward mode allows the solution of design problems that mimic some of the desirable properties appearing in natural oscillators. The reverse analysis mode facilitates a systematic exploration of the design space based on Pareto optimality concepts. The method is illustrated with two case studies: the automatic design of synthetic oscillators from a library of biological parts, and the exploration of design principles in 3-gene oscillatory systems.

Suggested Citation

  • Irene Otero-Muras & Julio R Banga, 2016. "Design Principles of Biological Oscillators through Optimization: Forward and Reverse Analysis," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-26, December.
    • Handle: RePEc:plo:pone00:0166867
    DOI: 10.1371/journal.pone.0166867
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    1. Naama Barkai & Stanislas Leibler, 2000. "Circadian clocks limited by noise," Nature, Nature, vol. 403(6767), pages 267-268, January.
    2. Michael B. Elowitz & Stanislas Leibler, 2000. "A synthetic oscillatory network of transcriptional regulators," Nature, Nature, vol. 403(6767), pages 335-338, January.
    3. Albert Goldbeter, 2002. "Computational approaches to cellular rhythms," Nature, Nature, vol. 420(6912), pages 238-245, November.
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    1. Bob Sluijs & Roel J. M. Maas & Ardjan J. Linden & Tom F. A. Greef & Wilhelm T. S. Huck, 2022. "A microfluidic optimal experimental design platform for forward design of cell-free genetic networks," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

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