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Stochastic Models for Genetic Evolution (BM)


Admission requirements

Basic probabilty theory. Basic analysis. Theory of Markov processes.


The goal of this course is to present a series of stochastic models from population dynamics capable of describing rudimentary aspects of DNA sequence evolution. Most of the course focuses on the Wright-Fisher model and its variations,
describing a population of individuals (= genes) of different types (= alleles) organised into a single colony and subject to resampling, mutation and selection, as well as populations organised into multiple colonies subject to migration. These models capture core phenomena arising in population genetics, including evolution and genealogy.

Course Objectives

Basic understanding of population genetics from a mathematical perspective.


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Mode of instruction

weekly lectures

Assessment method

Oral exam

Reading list

Lecture notes will be made available via Brightspace


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Contact via email: denholla[at]