Gene Drives
Designing and modeling CRISPR-based gene drive systems for population modification and suppression, including toxin-antidote systems and spatial dynamics.
Messer Lab
Evolutionary Biology & Population Genetics
Department of Computational Biology · Cornell University
Research
We are interested in a broad range of topics in evolutionary biology and population genetics. Our research focuses on rapid evolutionary processes, CRISPR gene drives, selective sweeps, population genomic inference methods, and the development of the SLiM simulation framework.
Our work combines theoretical modeling, computational methods, and experimental approaches to understand how populations evolve and adapt. We develop new statistical methods for population genomic inference and build simulation tools that are used by researchers worldwide.
Research Areas
Selective Sweeps
Developing methods to detect and characterize hard and soft selective sweeps from population genomic data, and understanding rapid adaptation.
SLiM Framework
Building and maintaining SLiM, a widely-used evolutionary simulation framework for forward-time population genetic modeling with complex scenarios.
Population Genomics
Statistical methods for inference from population genomic data, including the McDonald-Kreitman test, coalescent analysis, and machine learning approaches.
Recent Highlights
Nature Plants — Seed dormancy shapes gene drive dynamics in plants.
Science — Adaptations to water stress and pastoralism in the Turkana of northwest Kenya.
Mol. Biol. Evol. — SLiM 5: Eco-evolutionary simulations across multiple chromosomes and full genomes.
PLoS Comp. Biol. — Gaussian process emulation for modeling dengue outbreak dynamics.
Contact
Philipp W. Messer
Professor
Department of Computational Biology
Cornell University
404A Atkinson Hall
Ithaca, NY 14853
Join the Lab
We are always looking for motivated students and postdocs. If you are interested in joining the lab, please see open positions or contact Philipp directly.