Rice University - Department of Bioengineering; Rice University - Department of Systems, Synthetic, and Physical Biology Program; Rice University - Department of BioSciences
University of Texas at San Antonio - Department of Biomedical Engineering; Rice University - Department of Systems, Synthetic, and Physical Biology Program
We introduce cytoNet, a method to characterize multicellular topology from microscopy images. Accessible through a web-based interface, cytoNet quantifies the spatial relationships in cell communities using principles of graph theory, and evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in two applications relevant to regenerative medicine: quantifying the morphological response of endothelial cells to neurotrophic factors present in the brain after injury, and characterizing cell cycle dynamics of differentiating neural progenitor cells. The framework introduced here can be used to study complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior.
Mahadevan, Arun S. and Long, Byron L. and Hu, Chenyue Wendy and Ryan, David T. and Britton, George L. and Ligeralde, Andrew and Robinson, Jacob T. and Warmflash, Aryeh and Qutub, Amina Ann, cytoNet: Network Analysis of Cell Communities (March 15, 2019). Available at SSRN: https://ssrn.com/abstract=3353224 or http://dx.doi.org/10.2139/ssrn.3353224
This version of the paper has not been formally peer reviewed.
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