We employ quantitative experimental and computational methods to address the following:
Develop approaches to observe cellular metabolism at a spatial-temporal resolution
Reveal metabolic rewiring due to genomic mutations in cancer
Cancer immunometabolism
High-throughput metabolomics screening approaches
Cancer diagnosis via metabolomics and machine learning