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Systems Biology Modeling

Call for proposals opens: October 2026

The "Enabling Automated and Autonomous Robust High-Quality Systems Biology Modeling (Systems Biology Modeling)" campaign, led by Angela Cintolesi and Niaz Bahar Chowdhury, aims to make systems biology modeling faster, more reproducible, and more accessible to researchers working to understand and optimize microbial metabolism.

DNA strands being broken up into individual components as indicated by colored dots and strands

Building high-quality genome-scale metabolic models (GEMs), integrating proteomic and metabolomic data, and interpreting the results currently require specialized expertise and many manual steps, putting these approaches out of reach for many research groups.

Through this Computing, Analytics, and Modeling Community Science Campaign, EMSL will partner with invited researchers to integrate GEMs, multiomics data, and AI tools to identify, validate, and predict the metabolic pathways that explain observed microbial phenotypes.

Participants will bring existing multiomics datasets and expertise in experimental or computational microbial metabolism, working with EMSL staff and AI tools such as ChatGEM, PathwaySeeker, and the Mycelium AI co-scientist to discover new metabolic routes and identify strain engineering targets. The campaign will deliver reusable, evidence-traceable modeling workflows, prioritized pathways and engineering targets, and co-authored publications that support biotechnology and critical minerals and materials recovery, while laying the groundwork for autonomous phenotyping workflows on EMSL’s Anaerobic Microbial Phenotyping Platform.

The call for proposals opens October 2026, with work expected to begin in December. 

Stay tuned for more information, including an opportunity to submit a proposal.