Jerome Kelleher
BSc, PhD
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.
Recent publications
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Publisher Correction: Inferring whole-genome histories in large population datasets.
Journal article
Kelleher J. et al, (2019), Nature genetics
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Inferring whole-genome histories in large population datasets.
Journal article
Kelleher J. et al, (2019), Nature genetics, 51, 1330 - 1338
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Coupling Wright-Fisher and coalescent dynamics for realistic simulation of population-scale datasets
Journal article
Nelson D. et al, (2019)
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Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes.
Journal article
Haller BC. et al, (2019), Molecular ecology resources, 19, 552 - 566
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htsget: a protocol for securely streaming genomic data.
Journal article
Kelleher J. et al, (2019), Bioinformatics (Oxford, England), 35, 119 - 121