Albion College

Mathematics and Computer Science

Mathematics and Computer Science

COLLOQUIUM

Building Better Biological Models

Elizabeth Skubak Wolf

Randomness is inherent in many biological processes, from the dynamics of the populations in an ecosystem down to the systems of biochemical reactions occurring within a single cell. Therefore, when trying to analyze these processes, we might consider using a stochastic model — that is, one that includes some form of randomness.

Can stochastic models behave significantly differently from deterministic models? (Yes!) What might a stochastic model look like? How exactly does one use a stochastic model to say anything useful? We'll look at a few biological examples, introduce a particular stochastic model called a Markov chain, and see how, using a tool called Monte Carlo simulation, we can gain some insight into the biological systems we model.

Can stochastic models behave significantly differently from deterministic models? (Yes!) What might a stochastic model look like? How exactly does one use a stochastic model to say anything useful? We'll look at a few biological examples, introduce a particular stochastic model called a Markov chain, and see how, using a tool called Monte Carlo simulation, we can gain some insight into the biological systems we model.