10 papers analyzed
These studies suggest that the kinetics and thermodynamics of biochemical reactions can be studied and modeled using thermodynamic-kinetic modeling, in vivo data-driven approaches, bond graph methods, irreversible thermodynamics, stoichiometric approaches, thermodynamically consistent model calibration, fractal-like kinetics, time series data analysis, and mechanistic mathematical models.
Studying and modeling the kinetics and thermodynamics of biochemical reactions is crucial for understanding the dynamic behavior and regulation of biological systems. This involves developing mathematical models that accurately represent the rates of biochemical reactions and their thermodynamic constraints.
Thermodynamic-Kinetic Modeling (TKM) Formalism:
In Vivo Data-Driven Approaches:
Bond Graph Approach:
Irreversible Thermodynamics in Kinetic Modeling:
Stoichiometric and Kinetic Approaches:
Thermodynamically Consistent Model Calibration (TCMC):
Fractal-Like Kinetics in Crowded Environments:
Time Series Data for Kinetic Mechanisms:
Chemical Kinetics in Neuronal Signaling:
Modeling the kinetics and thermodynamics of biochemical reactions involves various approaches to ensure thermodynamic feasibility and accurate representation of reaction dynamics. Techniques such as thermodynamic-kinetic modeling, in vivo data-driven frameworks, bond graph approaches, and thermodynamically consistent model calibration are essential. Additionally, considering the unique conditions of intracellular environments and utilizing time series data can further refine these models. These methodologies collectively enhance our ability to understand and predict the behavior of complex biochemical systems.
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