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Research Fellows Directory

Sebastian Ahnert

Dr Sebastian Ahnert

Research Fellow

Organisation

University of Cambridge

Research summary

My research focuses on interdisciplinary applications of algorithmic information theory and network science, primarily to biology. Several problems interest me in this context. The first is the evolution of self-assembling structures in biology, such as protein complexes. There is a huge variety of different protein complexes, which I am classifying in a new way by using algorithmic information theory. This approach also allows me to enumerate all possible complexes that could possibly be built, either by nature, or by artificial protein engineering. My second interest is the structure of genotype-phenotype maps, which are the relationships between biological sequences (such as DNA) and the entities they encode (for example a protein). These maps strongly influence the paths that biological evolution takes, and we can study them through a variety of models, including a particularly tractable one that I have developed. Thirdly I am also very interested in complex networks, and in particular the algorithmic compression of networks, including gene regulatory networks in biology. Compression can help us to coarse-grain these very complicated structures, and tell us about important large-scale connection patterns. I also apply network science to new domains, such as history, food science, political science, and public health. Together with a historian I have analysed a network of the Protestant underground community under Queen Mary I of England, who famously executed many Protestants. Our analysis showed that network analysis can distinguish individuals with different roles in the community, including the sustainers of the network who provided support in the background.

Interests and expertise (Subject groups)

Grants awarded

Quantifying structural and functional complexity in biology

Scheme: University Research Fellowship

Dates: Apr 2014 - Mar 2017

Value: £299,381.79

Quantifying complexity: From pattern detection to self-assembling particles.

Scheme: University Research Fellowship

Dates: Apr 2009 - Mar 2014

Value: £510,560.80

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