{"id":15,"date":"2021-11-30T13:14:10","date_gmt":"2021-11-30T13:14:10","guid":{"rendered":"https:\/\/www.ebi.ac.uk\/research-beta\/lees\/home\/"},"modified":"2026-01-14T15:32:50","modified_gmt":"2026-01-14T15:32:50","slug":"home","status":"publish","type":"page","link":"https:\/\/www.ebi.ac.uk\/research\/lees\/","title":{"rendered":"Home"},"content":{"rendered":"
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Our group develops bioinformatic and mathematical modelling approaches to use sequencing data to better control pathogen threats. In particular, we study genome evolution, transmission, and the effects of vaccines and antimicrobial resistance in bacterial populations.<\/p>\r\n\n Edit<\/a>\n <\/div>\n <\/div>\n <\/div>\n
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\n John Lees<\/a>\n <\/h3>\n \n

\n Group Leader and Co-chair of Infection Biology Transversal Theme\n <\/p>\n \n \n \n \n

\n ORCID:<\/span>\n \n 0000-0001-5360-1254\n <\/a>\n <\/p>\n \n Edit\n <\/a>\n <\/article>\n <\/div>\n\n <\/div>\n<\/div>\n\n\n\n

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Our main website is www.bacpop.org<\/a>. Please see there for the most up-to-date information on the group<\/a>.<\/strong><\/p>\n\n\n\n

We want to understand how microbes (particularly pathogenic bacteria) evolve, becoming pathogenic and more transmissible. Understanding the mechanisms by which bacteria evolve and adapt to their environments is crucial to address many practical questions: designing drugs and vaccines against pathogens, optimising commercial processes, predicting future population dynamics and disease. The enormous diversity, but relatively simple biology of bacteria also offers an ideal system to answer fundamental questions in evolutionary biology. Do evolutionary processes repeat themselves? At what timescales do modes of evolution dominate? Can we predict future evolution?<\/em><\/p>\n\n\n\n

Secondly, we want to increase the performance and accessibility of evolutionary methods, including both bioinformatics and modelling. As well as increasing equity between regions, there are other advantages to making these techniques usable locally: global surveillance is more effective than concentrating resource in single regions; many regions without this technology have a higher burden of infectious disease due to existing inequities; data generators have unique knowledge of biases and important questions in their data, if they are able to analyse the data locally and without external support they can answer these questions more quickly, and more easily develop their own research and infection control programmes. We develop methods that can be easily run in a web-browser, on a typical laptop, and on high-performance GPUs.<\/p>\n\n\n\n

Research areas<\/strong><\/h2>\n\n\n\n

We currently work in the following overlapping topic areas:<\/p>\n\n\n\n