The Li Lab

The application of high-resolution mass spectrometry now enables the measurement in human samples the metabolome, lipidome and small molecules of dietary, microbial and environmental origins. This revolutionary information fills a major gap between genome and environment, with broad applications to diseases and precision medicine. We combine experimental approaches with computational algorithms that identify pathway patterns and integrate chemical reactions and biology. 

Current projects:

1. Probabilistic metabolite and network models for metabolomics. This includes the Mummichog Project, and addresses challenges in the assembly of information in metabolomics.
2. Reconstruction of biochemical networks and application to immunometabolism. The goal is to upgrade genome scale metabolic models by mass spectrometry data, via a combination of computational, genetic, cellular and isotope tracing techniques.
3. Multi-omics, multiscale modeling of human immunology. We are generating lakes of data from vaccine studies. Coupled with large-scale data mining and new generation of artificial intelligence, the resulting models shall aid vaccine development, immunotherapy and the fight against many diseases.