Mathematical Modeling in the Life Sciences Biomathematical Modeling

As modern life science research becomes ever more quantitative, the need for mathematical modeling becomes ever more important. A deeper and mechanical understanding of complicated biological processes can only come from the understanding of complex interactions at many different scales, for instance, the Cellular, individual organisms and population levels.

In this course, through case studies, we will examine some simplified and idealized mathematical models and their underlying mathematical framework so that we learn how to construct simplified representations of complex biological processes and phenomena. We will learn how to analyze these models both qualitatively and quantitatively and interpret the results in a biological fashion by providing predictions and hypotheses that experimentalists may verify.

As modern life science research becomes more quantitative, the need to build mathematical models becomes more and more important. A deep understanding of complex biological phenomena is ultimately based on understanding the complex biological interactions that occur at multiple temporal and spatial scales, for example, molecular, cellular, individual and population scales. By studying some cases, we will establish some simplified mathematical models and the basic mathematical framework behind them. At the same time, we will learn how to build simple representations of fundamental biological processes, and how to analyze these models quantitatively and qualitatively, and to interpret their results in a biological way, with a view to providing hypotheses for experimentalists to test and forecast.