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We have set out to devise a user-friendly generic platform, GemCell, for Generic Executable Modeling of Cells, based on whole, functioning cells.
Progress in computational modeling of cells has made it possible to predict metabolic byproduct secretion with bottom-up reconstructions of metabolic networks.
Modeling of cells on the basis of double- or multistaining image data for the cytoplasm and nucleus, and considering stress fibers and focal adhesions, remain as areas of future study.
Furthermore, in image-based 3D modeling of cells [8, 10, 16], the geometric change of an entire cell with the application of force or displacement that was seen in a numerical analysis was not compared with experimental results.
The present study provides a basis of adequate finite element modeling of cells under stretching of the vascular wall or substrate to investigate effects caused by the mechanical environment.
What this suggests is that the scope of collaboration in the life sciences is at once an experimental setting, focused on the complexity of the modeling of cells, and a feature of the formation of markets for sophisticated hardware, software and other informatic artifacts that are being used throughout the life sciences.
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Scientists are attempting to use models of ever-increasing complexity, especially in medicine, where gene-based diseases such as cancer require better modeling of cell regulation.
We illustrate how the method can be efficiently applied to nonlinear problems arising in modeling of cell communication.
Workshops for the 2003-04 year fall under the broad area of mathematical modeling of cell processes.
There has been extensive mathematical modeling of cell polarization as a special case of pattern formation in living systems.
Hence, stochasticity is often an essential feature for multi-level modeling of cell biological systems [ 23].
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