Dr 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.
A community-maintained standard library of population genetic models
Adrion JR. et al, (2020), eLife, 9
Accounting for long-range correlations in genome-wide simulations of large cohorts.
Nelson D. et al, (2020), PLoS genetics, 16
Efficiently Summarizing Relationships in Large Samples: A General Duality Between Statistics of Genealogies and Genomes
Ralph P. et al, (2020), Genetics, genetics.303253.2020 - genetics.303253.2020
Coalescent Simulation with msprime.
Kelleher J. and Lohse K., (2020), 2090, 191 - 230
Publisher Correction: Inferring whole-genome histories in large population datasets.
Kelleher J. et al, (2019), Nature genetics