Mathematical Oncology

Over 4600 new cancer cases are diagnosed every day in the U.S., and it is estimated that over half a million Americans will die from cancer this year. Due to the inherent complexity of tumor growth and development, purely experimental approaches fail to provide a complete picture. Thus, mathematical and computational techniques used to model how cancer cells grow, generate, and evolve, are becoming increasingly important in cancer research.

Our project will begin with an introduction to the field of mathematical oncology. Students will investigate several of the mathematical and computational techniques at the core of this field, and learn how mathematical analysis provides valuable, biological insights into concepts and data. We will focus on basic growth dynamics and deterministic models, including single-species growth and two-species competition, and show how these math equations are relevant for studying cancer. Students will use this knowledge to work on the design, refinement, and numerical simulation of tumor growth models across a variety of applications. For this project it will be useful to be familiar with concepts covered through Math 46 and have some knowledge of a programming language such as Matlab.