Journal article
A computational model of chemotaxis-based cell aggregation
BioSystems, v 93(3), pp 226-239
01 Sep 2008
PMID: 18602744
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We present a computational model that successfully captures the cell behaviors that play important roles in 2-D cell aggregation. A virtual cell in our model is designed as an independent, discrete unit with a set of parameters and actions. Each cell is defined by its location, size, rates of chemoattractant emission and response, age, life cycle stage, proliferation rate and number of attached cells. All cells are capable of emitting and sensing a chemoattractant chemical, moving, attaching to other cells, dividing, aging and dying. We validated and fine-tuned our
in silico model by comparing simulated 24-h aggregation experiments with data derived from
in vitro experiments using PC12 pheochromocytoma cells. Quantitative comparisons of the aggregate size distributions from the two experiments are produced using the Earth Mover’s Distance (EMD) metric. We compared the two size distributions produced after 24
h of
in vitro cell aggregation and the corresponding computer simulated process. Iteratively modifying the model’s parameter values and measuring the difference between the
in silico and
in vitro results allow us to determine the optimal values that produce simulated aggregation outcomes closely matched to the PC12 experiments. Simulation results demonstrate the ability of the model to recreate large-scale aggregation behaviors seen in live cell experiments.
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Details
- Title
- A computational model of chemotaxis-based cell aggregation
- Creators
- Manolya Eyiyurekli - Drexel University, Department of Computer Science, Philadelphia, PA 19104, United StatesPrakash Manley - Drexel University, School of Biomedical Engineering, Science and Health Systems, Philadelphia, PA 19104, United StatesPeter I. Lelkes - Temple UniversityDavid E. Breen - Drexel University, Computer Science
- Publication Details
- BioSystems, v 93(3), pp 226-239
- Publisher
- Elsevier
- Number of pages
- 14
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000258796800008
- Scopus ID
- 2-s2.0-48049109832
- Other Identifier
- 991014878167804721
UN Sustainable Development Goals (SDGs)
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Source: SDGs in the Output
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biology
- Mathematical & Computational Biology