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Ecology, evolution and epidemiology
In this course we will cover the basics of ecology, evolution, and epidemiology, with the lens and tools of physics.
We will show how concepts from nonlinear physics, stochastic processes, complex networks, random matrix theory and disordered systems can be leveraged to understand the complex dynamics of biological populations.
Whenever relevant, we will discuss experimental approaches and results to illustrate the covered topics, from epidemiological data and genomics to experiments of laboratory evolution of yeast and bacteria.
Syllabus
The course will cover :
- models of molecular evolution and their stochastic dynamics ;
- the neutral model of evolution ;
- models of rapidly adapting populations ; Lokta-Voltera models of ecology and their generalizations ;
- basic models of epidemiology (SEIR, etc) as well as their extension to structured populations.
Prerequisites
Stochastic processes; equilibrium statistical mechanics.
Evaluation
The exam will be a paper assignment where students working in small groups will present an article during an oral presentation.