Quantitative studies of cell metabolism are often based on large chemi- cal reaction network models. A steady-state approach is suited to ana- lyze phenomena on the timescale of cell growth and circumvents the problem of incomplete experimental knowledge on kinetic laws and parameters, but it should be supported by a correct implementation of thermodynamic constraints. In this chapter, we review the latter aspect, highlighting its computational challenges and physical insights. The sim- ple introduction of Gibbs inequalities avoids the presence of unfeasible loops allowing for correct timescale analysis, but leads to possibly non- convex feasible flux spaces whose exploration needs efficient algorithms. We briefly review the implementation of thermodynamics through variational principles in constraint-based models of metabolic networks.

The essential role of thermodynamics in metabolic network modeling: physical insights and computational challenges

Andrea De Martino;
2019

Abstract

Quantitative studies of cell metabolism are often based on large chemi- cal reaction network models. A steady-state approach is suited to ana- lyze phenomena on the timescale of cell growth and circumvents the problem of incomplete experimental knowledge on kinetic laws and parameters, but it should be supported by a correct implementation of thermodynamic constraints. In this chapter, we review the latter aspect, highlighting its computational challenges and physical insights. The sim- ple introduction of Gibbs inequalities avoids the presence of unfeasible loops allowing for correct timescale analysis, but leads to possibly non- convex feasible flux spaces whose exploration needs efficient algorithms. We briefly review the implementation of thermodynamics through variational principles in constraint-based models of metabolic networks.
2019
metabolic networks
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/423500
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