Using an adaptive gene network model for self-organizing multicellular behavior

Using the transient interleukin (IL)-2 secretion of effector T helper (Teff) cells as an example, we show that self-organizing multicellular behavior can be modeled and predicted by an adaptive gene network model. Incorporating an adaptation algorithm we established previously, we construct a network model that has the parameter values iteratively updated to cope with environmental change governed by diffusion and cell-cell interactions. In contrast to non-adaptive models, we find that the proposed adaptive model for individual Teff cells can generate transient IL-2 secretory behavior that is observed experimentally at the population level. The proposed adaptive modeling approach can be a useful tool in the study of self-organizing behavior observed in other contexts in biology, including microbial pathogenesis, antibiotic resistance, embryonic development, tumor formation, etc.


Published in:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5449-5453
Presented at:
34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego, CA, August 28 - September 1, 2012
Year:
2012
Publisher:
IEEE
Laboratories:




 Record created 2017-12-19, last modified 2018-09-13


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