Project Summary – Core C The Informatics and Computation Core (Core C) will play a three-pronged role in this Program Project Grant (PPG) investigating the role of perivascular adipose tissue (PVAT) as a central integrator of vascular health: i) service, ii) training and iii) development. Under the service component, Core C will oversee generation of, analyze, and visualize all bulk and single-cell genomic data required by Projects I-IV. Genes that are altered in the transition from health to high fat diet-induced hypertension in the principal cell types of the PVAT compartment will be identified, and trajectories of cellular perturbation along the health to disease continuum will be mapped. Voluntary training will be provided to all Project and Core personnel and trainees in use of cutting- edge tools in biological data visualization and network analysis. The development component will focus on building a predictive computational model of the transition of PVAT from a healthy state to an inflamed state in diet-associated hypertension, based on critical state transition theory. The model will integrate findings on: i) mechanisms of communication of vascular pressure to PVAT and the response of PVAT to this pressure (Project I); ii) the extent of innervation and the role of the nervous system in the functioning of PVAT in health and disease (Project II); iii) the effect of the PVAT microenvironment on immune function in the vascular neighborhood (Project III); and iv) the effect of mechanical forces on the adipogenic potential of PVAT (Project IV). This in silico model will provide a unified quantitative framework to generate and test novel hypotheses about the role of PVAT in health and under hypertension. The aims of Core C will be accomplished using free, open-source computational tools. Models and analysis scripts will be reproducibly recorded and shared across the PPG and beyond through open online portals like Github. Core C will also be able to provide significant cost savings to the PPG by centralizing execution and analysis of bulk and single-cell RNA-Seq experiments from all projects.