Associate Professor Jerome Kelleher
Robertson Fellow; Group Leader in Biomedical Data Science
My research revolves around developing efficient algorithms to solve fundamental problems in genomics, and implementing these algorithms in production quality, open source software. This programme takes advantage of the unique structure of genetic data, combining theoretical population genetics with classical computer science. I lead development of tskit, a growing library of fundamental operations for population and statistical genomics with a welcoming open source community.
I am an advocate for the importance of software in research and a member of the UK Research Software Engineer Association.
Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations.
Lauterbur ME. et al, (2023), eLife, 12
On the Genes, Genealogies, and Geographies of Quebec
KELLEHER J. et al, (2023), Science
A general and efficient representation of ancestral recombination graphs
Wong Y. et al, (2023)
link-ancestors: Fast simulation of local ancestry with tree sequence software
Tsambos G. et al, (2023)
Towards Pandemic-Scale Ancestral Recombination Graphs of SARS-CoV-2
Zhan S. et al, (2023)