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Illingworth Group

Microbial Evolution


Population genetics, evolution, pathogens

Research interests

In many pathogenic organisms, evolution can occur very rapidly, for example allowing a virus to escape from host immune mechanisms, or bacteria to become drug resistant. My research aims to understand the detail of these processes, using genome sequence data collected across multiple points in time.

Computational modelling plays a key role in my research, allowing statistical inferences to be made of where, and how, selection has acted to change the genetic make-up of a population. The common role of evolution across biological systems allows for the study of many different organisms; my recent work has addressed questions related to the evolution of yeast, of bacteria, and of the influenza virus.

Representative publications

  1. Abkallo, H. M., et al. (2017) Rapid identification of genes controlling virulence and immunity in malaria parasites. PLoS Pathogens, 13(7), e1006447–24.
  2. Sobel Leonard, A., et al. (2017) The effective rate of influenza reassortment is limited during human infection. PLoS Pathogens, 13(2), e1006203–26. 
  3. Illingworth, C. J., Fischer, A., & Mustonen, V. (2014) Identifying Selection in the Within-Host Evolution of Influenza Using Viral Sequence Data. PLoS Computational Biology, 10(7), 1–13.
  4. Illingworth, C. J., & Mustonen, V. (2012) Components of Selection in the Evolution of the Influenza Virus: Linkage Effects Beat Inherent Selection. PLoS Pathogens, 8(12), e1003091.
  5. Illingworth, C. J., & Mustonen, V. (2011) Distinguishing driver and passenger mutations in an evolutionary history categorized by interference. Genetics189(3), 989–1000.

>> Full list of publications on PubMed

Page updated : 26 Oct 2017

Contact details

Group leader : Dr Chris Illingworth

Department of Genetics,
University of Cambridge,
Downing Street,
Cambridge CB2 1EH,
United Kingdom


Tel.: +44 (0)1223 766336

Group members