Abstract: Network biology has been increasingly utilized to model large-scale Omics data for its great potential to identify novel key variables and interacting pathways underlying a biological function, system or state under examination. Often a single type of molecular networks (gene coexpression network, gene causal network, protein interaction network) is used for a particular Omics study. For complex biological systems or diseases, any single type of networks may be insufficient to fully characterize the underlying Omics data. Multiscale network modeling emerges as a more powerful way to dissect complex molecular interactions and regulations in such complex systems or diseases for identification of novel pathways and targets that are essential to maintain biological functions, initiate disease process or drive disease progression. In this talk, I will introduce our latest progresses on constructing and analyzing multiscale molecular networks including weighted interaction network analysis (WINA), multiscale embedded gene coexpression network analysis (MEGENA) and differential gene correlation analysis (DGCA), and highlight their applications to cancer, diabetes and neurodegenerative diseases.