The overall goal of the Systems Biology Core (Core C) is to provide computational genomics and machine learning (ML) modeling expertise to the 3 projects in the P50. This expertise will utilize high dimensional datasets generated by the research projects including scRNA-seq, scATAC-seq and proteomics. These datasets will be leveraged using a suite of computational tools, either individually or in an integrated manner to address major biological questions posed by the research projects. Thus, the Core C team will function as an essential collaborative group that will help to test hypotheses and to generate predictions as well as causal inferences underlying the pathophysiology of distinct manifestations of SSc (Project 1) including SSc-ILD (Project 2) and SSc-PAH (Project 3). The aims of Core C include the inference of cell-intrinsic TF-directed genomic programs and cell-extrinsic, intercellular signaling pathways underlying SSc cellular states as well as the identification of gene/protein and module-centric predictive biomarkers of SSc outcomes. These will be enabled via a wide range of state-of-the- art computational genomics and machine learning approaches. Overall, Core C is strongly integrated with the key biological objectives of all 3 projects.