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Inference of analytical thermodynamic models for biological networks

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  • Biology
  • Chemistry
  • Computer Science
  • Medicine
  • Physics


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 an input, the method requires a number of steady states (i.e. an equilibria cloud in the 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)

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