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Inference of analytical thermodynamic models for biological networks

Author

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  • Chiavazzo, Eliodoro
  • Fasano, Matteo
  • Asinari, Pietro

Abstract

We present an automated algorithm for inferring analytical models of closed reactive biochemical mixtures, on the basis of standard approaches borrowed from thermodynamics and kinetic theory of gases. As input, the method requires a number of steady states (i.e. an equilibria cloud in phase–space), and at least one time series of measurements for each species. Validations are discussed for both the Michaelis–Menten mechanism (four species, two conservation laws) and the mitogen-activated protein kinase–MAPK mechanism (eleven species, three conservation laws).

Suggested Citation

  • Chiavazzo, Eliodoro & Fasano, Matteo & Asinari, Pietro, 2013. "Inference of analytical thermodynamic models for biological networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1122-1132.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:5:p:1122-1132
    DOI: 10.1016/j.physa.2012.11.030
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    References listed on IDEAS

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    1. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
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    Cited by:

    1. Luigi Ventola & Gabriele Curcuruto & Matteo Fasano & Saverio Fotia & Vincenzo Pugliese & Eliodoro Chiavazzo & Pietro Asinari, 2016. "Unshrouded Plate Fin Heat Sinks for Electronics Cooling: Validation of a Comprehensive Thermal Model and Cost Optimization in Semi-Active Configuration," Energies, MDPI, vol. 9(8), pages 1-16, August.
    2. Asinari, Pietro & Chiavazzo, Eliodoro, 2014. "The notion of energy through multiple scales: From a molecular level to fluid flows and beyond," Energy, Elsevier, vol. 68(C), pages 870-876.
    3. Romain Bocher, 2023. "Causal Entropic Forces, Narratives and Self-organisation of Capital Markets," Journal of Interdisciplinary Economics, , vol. 35(2), pages 172-190, July.

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