Work

Simulation-based Modeling of Biological Traits and Inference from the Ancestral Recombination Graph

Year: 2023

Type: dissertation

Abstract: Understanding genetic diversity lies at the heart of population genetics. In this thesis, we explore the approach of individual-based models to study dormancy and large stochastic variance of offspring distributions both under the influence of positive selection. We then continue to assess the suitability of graph neural networks to capture some of the diversity structured in the form of the ancestral recombination graph.

Authors: Korfmann, Kevin, Tellier, Aurélien 1979-, Technische Universität München

Language: English

Topic: Evolution and Genetic Dynamics

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: Imperial College London, Deutsche Forschungsgemeinschaft, Austrian Science Fund, International Graduate School of Science and Engineering

Awards: G5699669439, G6470831837

OpenAlex ID: W6987158894

Cites: 261

Cited by:

Related to: 10