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Dr Christophe Dessimoz
Room 631
Darwin Building
Gower Street
Tel: +44 20 7679 0079 (Int. 30079)
  • Lecturer
  • Genetics, Evolution & Environment
  • Div of Biosciences
  • Faculty of Life Sciences

My first degree was in Biology at ETH Zürich, Switzerland. After half-year stints at Northwestern University (USA), at Tsinghua University (China), and at Chulalongkorn University (Thailand), I returned to ETH Zürich where I obtained my PhD in 2009 for contributions to comparative genomics. I went on to become a postdoc, later senior research associate at ETH Zurich. In 2011, I moved to the EMBL-European Bioinformatics Institute in Hinxton as visiting scientist in Nick Goldman's group, funded by an advanced researcher fellowship from the Swiss National Science foundation. Since 2013, I am a joint lecturer at the Department of Genetics, Evolution, and Environment and the Department of Computer Science.

Research Summary

Lab website: http://lab.dessimoz.org

At the interface between biology and computer science, my research seeks to better understand evolutionary and functional relationships between genes, genomes, and species. I aspire to unravel general principles of molecular evolution and to apply this knowledge to better understand molecular function and dysfunction, using statistical and computational methods. The key questions underlying my research are:

  • How can we best extrapolate our current knowledge of molecular biology, concentrated in just a handful of model organisms, to the rest of life?
  • Conversely, how can we exploit the wealth and diversity of life to better understand human biology and disease?
  • Can we meaningfully summarise the evolutionary history of species into a small number of tree topologies that capture both the vertical inheritance and most important events of non-vertical inheritance?

I tackle these problems by developing statistical and computational methods and applying them to large-scale genomic data. This process combines biological aspects in the early stages (e.g. problem statement, identifying relevant empirical observations, determining dependable benchmarks and controls), statistical, algorithmic, and computational aspects in the middle (e.g. model formulation, programming, scaling up), and biological aspects again at the end in the interpretation of the results.

Academic Background
2009 PhD Doctor of Philosophy – Computer Science Eidgenössische Technische Hochschule Zürich
2003 MSc Master of Science – Biology Eidgenössische Technische Hochschule Zürich
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