From microbial interactions to community dynamics

Mathematical modeling

Interactions are at the core of understanding community dynamics across many scales in biology. From molecular interaction networks, we have learned that organization and evolution of interactions provide higher order properties to the cell, such as robustness, adaptability, resilience, noise handling and reactivity. This is also applicable to ecological communities. The interplay between species in time and space allows for emergent properties to arise – selforganization and pattern formation are the rule, which govern in turn community processes. It is however not straight forward to identify and quantify interactions. Particularly for microbial habitats these are commonly elusive. But given the key importance of microbial communities for our lives, their involvement ranges from geochemical cycles to human health issues, it is imperative to get a grip on microbial interactions, as well as their structure and dynamics in a large scale manner.

We contribute here with a highly interdisciplinary approach integrating methods from the fields of systems biology, complex systems, bioinformatics, ecology, genetics and microbiology. We are interested in topics concerning microbial community organization and how it influences community robustness, resilience, productivity, biodiversity and community roles.

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