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J Phys Chem B. 2010 Dec 16;114(49):16298-303. doi: 10.1021/jp108764b. Epub 2010 Nov 1.

Parameter balancing in kinetic models of cell metabolism.

Author information

1
Humboldt-Universität zu Berlin, Institut für Biologie, Theoretische Biophysik, Invalidenstrasse 42, D-10115 Berlin.

Abstract

Kinetic modeling of metabolic pathways has become a major field of systems biology. It combines structural information about metabolic pathways with quantitative enzymatic rate laws. Some of the kinetic constants needed for a model could be collected from ever-growing literature and public web resources, but they are often incomplete, incompatible, or simply not available. We address this lack of information by parameter balancing, a method to complete given sets of kinetic constants. Based on Bayesian parameter estimation, it exploits the thermodynamic dependencies among different biochemical quantities to guess realistic model parameters from available kinetic data. Our algorithm accounts for varying measurement conditions in the input data (pH value and temperature). It can process kinetic constants and state-dependent quantities such as metabolite concentrations or chemical potentials, and uses prior distributions and data augmentation to keep the estimated quantities within plausible ranges. An online service and free software for parameter balancing with models provided in SBML format (Systems Biology Markup Language) is accessible at www.semanticsbml.org. We demonstrate its practical use with a small model of the phosphofructokinase reaction and discuss its possible applications and limitations. In the future, parameter balancing could become an important routine step in the kinetic modeling of large metabolic networks.

PMID:
21038890
PMCID:
PMC2999964
DOI:
10.1021/jp108764b
[Indexed for MEDLINE]
Free PMC Article

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