Theoretical science is a mindset and our group develops mathematical, statistical, computational approaches, and concepts to help us understand how cells make decisions and how biological systems organise themselves. We study living systems across the whole Tree of Life, ranging from bacteria to complex multicellular organisms. We use habits of multidisciplinary practice, curiosity, tenacity, and exceptional research training to understand fundamental questions in biology and to improve people’s lives.
The Theoretical Systems Biology Group brings together a diverse group of people with the common goal to use mathematical and statistical methods to seek to understand how cells compute.We are always looking for curiosity driven individuals who care about their research and the impact it has for life on our planet. There is no blueprint for what makes a successful researcher in this area, so please do not worry about formal requirements. If you are interested and ready to explore please get in touch. If you want to understand living systems and innovate, we would love to hear from you.
The Theoretical Systems Biology group started in October 2003 at Imperial College London; it is led by Michael Stumpf. Michael has a background in theoretical physics and switched to biology in 1999 to work with Bob May in Zoology in Oxford. The group has had its home in Life Science Departments ever since. We have always tried to do three things:
- Tackle exciting and important scientific problems in the life-sciences that require or benefit from a theoretical perspective.
- Do science in a way that benefits society and that has the potential to change the world for the better.
- Create a diverse and supportive atmosphere for early career researchers to embark on a research career.
We continue to work towards these aims. And since September 2018 we do so at the University of Melbourne in Australia.
Our work is firmly rooted in studying important biological problems and we do so across the tree of life, from bacteria to complex multicellular organisms. A common theme is to understand how cells process information and change their behaviour. As a direct consequence of the group’s biological interests and ambitions our theoretical and computational toolset has been unusually wide-ranging. Methodologically we apply and develop tools from statistical physics, pure and applied mathematics, Bayesian statistics and machine learning, information theory, and computer science to gain insights into the organisation and evolution of living systems.
Featured research
2022
Noise distorts the epigenetic landscape and shapes cell-fate decisions Journal Article
In: Cell Systems, vol. 13, no. 1, pp. 83-102.e6, 2022, ISSN: 2405-4712.
