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International Conference on Computational Methods in Systems Biology

CMSB 2014: Computational Methods in Systems Biology pp 244–247Cite as

Extensible and Executable Stochastic Models of Fatty Acid and Lipid Metabolism

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

Abstract

Stochastic reaction-centric views are suitable for exploring hybrid minimal mechanism-statistical models of fatty acid and lipid metabolism, the basis of de novo lipogenesis. In this work, we demonstrate a reduced model for the core fatty acid synthesis and elongation process with a regulatory mechanism. This allows us to explore fatty acid profiles from lipid metabolomics data. This is part of a current study to assess the programming languages for capturing inherent probabilistic behaviour of the hierarchical chemical transformations of complex lipid species.

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Author information

Authors and Affiliations

  1. Cambridge Computational Biology Institute, Department of Applied Mathematics and Theoretical Physics, University of Cambridge, UK

    Argyris Zardilis & James Smith

  2. SynthSys, University of Edinburgh, C.H. Waddington Building, UK

    Argyris Zardilis

  3. Cambridge Systems Biology Centre, University of Cambridge, UK

    João Dias

  4. Department of Biochemistry, University of Cambridge, UK

    João Dias & James Smith

  5. MRC Human Nutrition Research, Elsie Widdowson Laboratory, Cambridge, UK

    Argyris Zardilis, Animesh Acharjee & James Smith

Authors
  1. Argyris Zardilis
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  2. João Dias
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  3. Animesh Acharjee
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  4. James Smith
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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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© 2014 Springer International Publishing Switzerland

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Zardilis, A., Dias, J., Acharjee, A., Smith, J. (2014). Extensible and Executable Stochastic Models of Fatty Acid and Lipid Metabolism. 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_18

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  • DOI: https://doi.org/10.1007/978-3-319-12982-2_18

  • 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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