Computational systems biology
In this research theme we use mathematical models to further understand the functioning of microbial systems. We do so by studying genomes of microbes and analysing and combining multiple information types.
We are especially interested in:
- How genome information leads to function.
- How microbial metabolic processes are regulated and adapt in extant species.
- How microbial organisms and ecosystems respond to (a)biotic environmental cues.
- How they can be manipulated to enhance the yield of desired products or to diminish their pathogenicity.
Our computational methods include genome-scale metabolic modelling (GEM) of single organisms and communities, kinetic models based on differential equations and statistical methods for omics data exploration and integration.
Research themes
Computational systems biology
We use mathematical models to study genomes of microbes as well as their functioning.
Systems health
In this theme, we aim to predict disease onset, progression, and remission by analysing patient data.
Semantic systems biology
We link biological data in such a way computers can better understand, combine, and use them in life sciences.
Microbial systems and synthetic biology
We develop novel technologies of DNA modification and genome engineering to re-design microbes for biotechnological application.
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