An agent-based model approach to multi-phase life-cycle for contact inhibited, anchorage dependent cells

Cellular agent-based models are a technique that can be easily adapted to describe nuances of a particular cell type. Within we have concentrated on the cellular particularities of the human Endothelial Cell, explicitly the effects both of anchorage dependency and of heightened scaffold binding on t...

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Bibliographic Details
Published in:Interdisciplinary sciences : computational life sciences 2014-12, Vol.6 (4), p.312-322
Main Authors: Hoehn, Ross. D., Schreder, Ashley. M., Rez, Mohammed Fayez Al, Kais, Sabre
Format: Article
Language:English
Subjects:
Algorithms
Anchorages
Binding
Biomedical and Life Sciences
Cell Cycle
Cell Movement
Cellular
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Appl. in Life Sciences
Computer Simulation
Control systems
Dynamical systems
Dynamics
Endothelial cells
Endothelial Cells - physiology
Guided Tissue Regeneration
Health Sciences
Humans
Life Sciences
Mathematical and Computational Physics
Mathematical models
Medicine
Models, Biological
Original Article
Statistics for Life Sciences
Theoretical
Theoretical and Computational Chemistry
Tissue Scaffolds
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Summary:Cellular agent-based models are a technique that can be easily adapted to describe nuances of a particular cell type. Within we have concentrated on the cellular particularities of the human Endothelial Cell, explicitly the effects both of anchorage dependency and of heightened scaffold binding on the total confluence time of a system. By expansion of a discrete, homogeneous, asynchronous cellular model to account for several states per cell (phases within a cell’s life); we accommodate and track dependencies of confluence time and population dynamics on these factors. Increasing the total motility time, analogous to weakening the binding between lattice and cell, affects the system in unique ways from increasing the average cellular velocity; each degree of freedom allows for control over the time length the system achieves logistic growth and confluence. These additional factors may allow for greater control over behaviors of the system. Examinations of system’s dependence on both seed state velocity and binding are also enclosed.
ISSN:1913-2751
1867-1462
DOI:10.1007/s12539-012-0236-4