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Integration of Reaction Kinetics Theory and Gene Expression Programming to Infer Reaction Mechanism

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

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Abstract

Mechanistic mathematical models of biomolecular systems have been used to describe biological phenomena in the hope that one day these models may be used to enhance our fundamental understanding of these phenomena, as well as to optimize and engineer biological systems. An evolutionary algorithm capable of formulating mass action kinetic models of biological systems from time series data sets was developed for a system of n-species. The strategy involved using a gene expression programming (GEP) based approach and heuristics based on chemical kinetic theory. The resulting algorithm was successfully validated by recapitulating a nonlinear model of viral dynamics using only a “noisy” set of time series data. While the system analyzed for this proof-of-principle study was relatively small, the approach presented here is easily parallelizable making it amenable for use with larger systems. Additionally, greater efficiencies may potentially be realized by further taking advantage of the problem domain along with future breakthroughs in computing power and algorithmic advances.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. 1137249 and 1517133.

Supporting Information.

Mathematica source code and instructions are available from http://www.rslabs.org under a BSD open source license.

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Author notes

  1. Jason R. White

    Present address: Department of Chemical Engineering, University of California, One Shields Avenue, Davis, California, USA

Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Connecticut, USA

    Jason R. White & Ranjan Srivastava

Authors
  1. Jason R. White
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  2. Ranjan Srivastava
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Corresponding author

Correspondence to Ranjan Srivastava .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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White, J.R., Srivastava, R. (2017). Integration of Reaction Kinetics Theory and Gene Expression Programming to Infer Reaction Mechanism. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_4

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  • DOI: https://doi.org/10.1007/978-3-319-55849-3_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55848-6

  • Online ISBN: 978-3-319-55849-3

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