Virtual cells for microbial communities
Mechanistic, data-constrained models of microbial physiology to understand and design microbial communities.
Microbial cells must allocate limited resources among growth, maintenance, and responses to a changing environment. We build mechanistic yet data-constrained virtual cell models that integrate multi-omics data, such as proteomics and metabolomics, to capture these trade-offs quantitatively, and we use them to reason about how microbial communities are assembled and how they can be designed.
Recent work in this area includes multi-omics analysis of the temporal scales of carbon metabolism in the cyanobacterium Synechococcus elongatus under light disturbance (PRX Life, 2025).
TODO (Song): expand with current projects, collaborators, and funding.
People
- Song Feng — Assistant Professor & Principal Investigator