"Simulating chemical interactions between cells in human tissue using ontology"
While cell mapping and gene mapping are on the radar to have in-depth knowledge about the human body, it is equally important to understand the interactions happening at the cellular and tissue level. In this project, we are utilizing the HubMap data to understand the functionality of each cell in a functional tissue unit. Once the HubMap (The Human BioMolecular Atlas Program) data is attained, we use PhysiCell, a physics-based simulator, to create a similar 3D environment that integrates the agent-based modeling (ABM). Our first step in the project is to fetch the single-cell RNA(scRNA seq) sequence data of healthy or diseased tissue. Once the data is analyzed and reduced to machine-readable format, we filter out the mapped cells that act as secretors and cells that act as receivers. These sets of chemical secretors and receivers respond to chemicals in varied ways. Combining chemical communication graphs for the actions obtained in the biological world and multiscale agent-based modeling will help us visually interpret the chemical interactions between the cells and functional units of human tissue. The goal is to develop mathematical models that visually interpret the chemical interactions between cells and the functional unit of each human tissue.
Additional authors: Paul Macklin, Indiana University, Bloomington Katy Borner, Indiana University, Bloomington