The aim of this course is to provide an integrated view of data-driven hypothesis generation through machine learning integration methods, biological graph / network analysis and genome-scale metabolic models. A general description of different methods for analyzing different omics data (e.g. transcriptomics and genomics) will be presented with some of the lectures discussing key methods and pitfalls in their integration.