The spatial organization of chromatin within the eukaryotic nucleus is critical in regulating key cellular functions, such as gene expression, and its disruption can lead to disease. Advances in experimental techniques, such as Hi-C and microscopy, have significantly enhanced our understanding of chromatin's intricate and dynamic architecture, revealing complex patterns of interaction at multiple scales. Along with experimental methods, physics-based computational models, including polymer phase separation and loop-extrusion mechanisms, have been developed to explain chromatin structure in a principled manner. Here, we illustrate genomewide applications of these models, highlighting their ability to predict chromatin contacts across different scales and to spread light on the underlying molecular determinants. Additionally, we discuss how these models provide a framework for understanding alterations in chromosome folding associated with disease states, such as SARS-CoV-2 infection and pathogenic structural variants, providing valuable insights into the role of chromatin architecture in health and disease.