I typically have a research group of around ten students, postdocs and staff scientists, and am also involved in a large number of collaborative projects. Applicants for postdoc or visiting positions are welcome at any time; please email me with an outline of what you are interested in doing and why it would fit with my group. A list of current projects can be found at my research group page.
In the past I have led a number of large scale genomics projects, including the 1000 Genomes Project (with David Altshuler at the Broad Institute) and the UK10K project, both of which completed in 2015, and the gorilla reference sequencing project. Previously I worked on sequence analysis software including hidden Markov model (HMM) methods for gene finding and protein similarity detection, jointly authoring a book Biological Sequence analysis with Sean Eddy, Anders Krogh and Graeme Mitchison. I also helped establish a number of reference genomic databases including WormBase for C.elegans biology (using the ACeDB software I co-developed with Jean Thierry-Mieg), Pfam, TreeFam and Ensembl.
My timeline
Al Kindi Professor of Genetics, University of Cambridge and Associate Faculty, Wellcome Sanger Institute
Wellcome Trust Sanger Instititute: Senior Group Leader and various roles including Head of Informatics, Deputy Director, Joint Head of Human Genetics, Acting Head of Computational Genomics
MRC Laboratory of Molecular Biology: staff member/junior group leader working on the C. elegans genome project
Postdoc in neural networks at Stanford University
PhD on the development and organisation of the C.elegans nervous system at MRC Laboratory of Molecular Biology
Fulbright fellowship in biophysics at Harvard University
BA in Mathematics at Cambridge University
Quick links
Programmes and Facilities
My publications
Whole genome sequence phylogeny of over 50 Lake Malawi cichlid species that we have sequenced, with illustrations of focal species for which we are collecting population samples. Speciation is very recent or even ongoing, with divergence between species of 0.1% to 0.3% compared to diversity within species of 0.05% to 0.1%.
Rarecoal uses rare segregating variants across a set of population samples to infer population separation times and mean effective population sizes, using a coalescent likelihood approximation.
