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International Conference on Computational Methods in Systems Biology

CMSB 2014: Computational Methods in Systems Biology pp 225–238Cite as

Optimization Based Design of Synthetic Oscillators from Standard Biological Parts

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8859))

Abstract

We consider the problem of optimal design of synthetic biological oscillators. Our aim is, given a set of standard biological parts and some pre-specified performance requirements, to automatically find the circuit configuration and its tuning so that self-sustained oscillations meeting the requirements are produced. To solve this design problem, we present a methodology based on mixed-integer nonlinear optimization. This method also takes into account the possibility of including more than one design objective and of handling both deterministic and stochastic descriptions of the dynamics. Further, it is capable of handling significant levels of circuit complexity. We illustrate the performance of this method with several challenging case studies.

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Author information

Authors and Affiliations

  1. BioProcess Engineering Group, IIM-CSIC, Spanish Council for Scientific Research, Vigo, Spain

    Irene Otero-Muras & Julio R. Banga

Authors
  1. Irene Otero-Muras
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  2. Julio R. Banga
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Editor information

Editors and Affiliations

  1. Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, M1 7DN, Manchester, UK

    Pedro Mendes , Joseph O. Dada  & Kieran Smallbone ,  & 

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Otero-Muras, I., Banga, J.R. (2014). Optimization Based Design of Synthetic Oscillators from Standard Biological Parts. In: Mendes, P., Dada, J.O., Smallbone, K. (eds) Computational Methods in Systems Biology. CMSB 2014. Lecture Notes in Computer Science(), vol 8859. Springer, Cham. https://doi.org/10.1007/978-3-319-12982-2_16

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  • DOI: https://doi.org/10.1007/978-3-319-12982-2_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12981-5

  • Online ISBN: 978-3-319-12982-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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