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Our study has important implications as targeting c-Myc has unique benefits specific to cellular compartments in models representing cellular heterogeneity.
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Many simulator tools capitalized on the "noisy" behavior of some systems and used formal models to represent cellular activities as temporal trajectories.
An alternative approach is agent based modeling (ABM), which relies on a predefined logical programming language to implement source code representing cellular processes within a software framework.
Some in silico whole cell models can now represent cellular functions mechanistically with a reasonable degree of accuracy [ 11, 12].
This is necessary to find suitable attractors of the network model representing the cellular phenotypes.
To represent cellular membranes, their models typically use a small 3D volume on the exterior of the domain.
In this regard, 3D models of tumor-cell invasion [28] represent cellular dynamics and architecture of tumors far better than 2D monolayer cultures in which cells spread and glide across the plastic surface.
Given a completely annotated genome, the challenges in metabolic modeling have been application of appropriate constraints that represent cellular physiology and, thereafter, solving the resulting set of equations.
By means of model analysis, one can reveal the existence of attractors that represent cellular phenotypes and understand the dynamics between states [ 27- 29].
These models represent several types of cellular processes, including models of electrophysiology, metabolism, signal transduction and mechanics.
Alternatively, these peaks might represent cellular debris.
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