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The evolution of variables, such as molecular concentrations, is represented using ordinary differential equations and cellular behaviour using the agent-based framework.
Instead of focusing on the quality of the estimated values of the kinetic parameters, it has been argued in [ 20] that matching predicted and experimental observations of molecular concentrations is the right thing to do due to the 'sloppiness' of biochemical reaction systems (different combinations of parameter values may essentially lead to the same concentration dynamics).
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Molecular concentrations are important for various processes such as the embryogenesis, positional homeostasis and its relation to cell energy expenditure, cell torque, cell deformation, and more.
Molecular concentrations were transformed to a log2 scale to assess their total magnitude of change.
The molecular concentrations are determined by a group of rate equations.
Changes in the molecular concentrations are described by these models by mass action or Michaelis-Menten kinetic rate-law equations.
Stochasticity plays important roles in many molecular networks when molecular concentrations are in the range of 0.1 μM to 10 nM (about 100 to 10 copies in a cell).
In our case, suppose that when all molecular concentrations are below a threshold x i t h, the cell should not die; for at least one concentration greater than its fixed threshold x i t h, the cell should die.
In order to resolve this issue for systems where molecular concentrations are relatively large, as a next step we propose a novel delay differential equation (DDE) methodology for solving problems with subsequent translocations and intermediate reactions, such as Scenario 5.
The stochasticity originates intrinsically from the small copy numbers of the molecular species in a cell, which frequently occur when molecular concentrations are in the range of 0.1 μM to 1 nM (typically from about 100 to 10 copies in a cell) [ 2, 6].
Molecular concentration is the number of molecules of a particular component per unit volume.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com