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Kinetic parameters of biochemical systems can be altered by mutations resulting in perturbed activities and are subject to fluctuations due to variations in the environment (pH, temperature, ionic strength).
In this way, natural biochemical systems can be better understood.
Using this method, nonstationary behavior of biochemical systems can be analyzed.
Therefore, behaviours of target biochemical systems can be predicted and reasoned qualitatively in silico with the support of QR [ 30].
Moreover, topologies of biochemical systems can be identified [ 29, 65] and parameter values can be numerically determined or estimated [ 32, 43].
In this research, we show how the identification of biochemical systems can be performed and evolved in an integrative manner by reusing, composing, and evolving biochemical modules qualitatively and by mutating kinetic rates quantitatively.
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Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models.
Thus, the impact of sub-cellular organization on the temporal and spatial evolution of biochemical reaction-diffusion systems can be studied using MCell.
These types of systems can be conceptualized as "reagent-limited", typically lacking the photo- or biochemical energy to induce drastic structural modifications, much less mineralization.
Distribution systems can be hopeless.
This shortcoming arises partly because the models have not been examined through in vitro biochemical reconstitution, where the parameters of the system can be tightly controlled and the physical properties of the clusters can be analyzed in detail.
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