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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Advisors:
Melissa Kemp, PhD (Georgia Institute of Technology)
Todd McDevitt, PhD (Gladstone Institute of Cardiovascular Disease)
Thesis Committee Members:
Michael Levin, PhD (Tufts University)
Krishnendu Roy, PhD (Georgia Institute of Technology)
Brani Vidakovic, PhD (Georgia Institute of Technology)
Eberhard Voit, PhD (Georgia Institute of Technology)
Computational analysis of the intercellular network and its influence on driving spatial differentiation.
Gap junctions and their protein components, connexins, are associated with multiple cellular functions including metabolic coupling, tumor suppression, and modulation of cell signaling. This diversity of function results in gap junctions being crucial for regulating differentiation during development, while disruption of gap junctions is implicated in the pathology of numerous diseases. Specifically, inhibition of gap junctions in pluripotent stem cells has been reported to abrogate the maintenance of pluripotency, suggesting the gap junction intercellular network may provide a novel mechanism to promote differentiation within cell populations. However, the ability to interrogate intercellular communication networks in a spatiotemporal manner is currently limited. Theoverall objective of this proposal is to determine spatiotemporal characteristics of the gap junction network that drive differentiation in embryonic stem cell colonies. Computational modeling provides a useful tool for analyzing the complex dynamics of various factors that affect intercellular communication, such as cell cycle state and connexin expression, and the resultant emergence of spatial patterns within the network. The central hypothesis is that spatial differentiation within pluripotent colonies is a function of dynamic intercellular communication. Convergent experimental and computational modeling techniques will be applied to assess how modulations to the intercellular network contributes to differentiation potential.
