What we do

In the Computational Evolution Group, we develop phylogenetic tools in order to understand evolutionary processes. Using our phylogenetic methods, we aim to improve our understanding of past evolutionary and population dynamic processes on different scales. We address questions in a number of fields, focusing on epidemiology, public health and medicine, ecology and evolution, and language evolution. In our daily work, we define and analyse stochastic models, implement computational methods, analyse empirical data, and discuss our new insights with clinicians, and public-health policy makers, as well as ecologists and palaeontologists.

Find out about the Group’s activities

Main publications 2019

  • Mitov V et al.
    Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models
    PNAS, doi: 10.1073/pnas.1813823116
  • Rasmussen DA and Stadler T.
    Coupling adaptive molecular evolution to phylodynamics using fitness-dependent birth-death models
    eLife, doi: 10.7554/eLife.45562
  • Vaughan TG et al.
    Estimating Epidemic Incidence and Prevalence from Genomic Data
    Molecular Biology and Evolution, doi: 10.1093/molbev/msz106


University basel

Tanja Stadler
Computational Evolution Group
D-BSSE, ETH Zurich, Basel
Group Webpage

Domain(s) of activity:

  • Evolution and phylogeny
  • Biostatistics
  • Evolutionary biology
  • Infectious diseases
  • Mathematical modelling
  • Next generation sequencing
  • Phylogeny
  • Phylogenetic tree analysis (natural selection)
  • Single-cell biology
  • Software engineering

Domain(s) of application:

  • Basic research
  • Medicine and health