Cancer is a disease whose complexity is amenable to study by systems biology approaches. A key focus of the development of systems biology approaches to make a clinical impact is the integration of clinical and molecular data from cancer patients into computational frameworks. Mathematical models are being developed to address this issue by understanding the complexities at the gene, pathway, cellular and tissue level. This book chapter reviews the scope of mathematical and computational models in cancer research. It covers a group of related models addressing topics at different biological scales including DNA mutation, DNA repair, signal transduction and cell cycle, cell invasion, cell proliferation, cell migration, avascular tumor formation, vascular tumor growth, and angiogenesis.