Modeling Metabolism for Precision Medicine

Personalized medicine, or Precision medicine, aims to assess medical risks, monitor, early diagnose and treat patients based on the genetic background, molecular signatures and clinical phenotyping from individual patient or patients subgroup. PM holds the promise for improving healthcare while also lowering costs. As a promoter of PM, high-throughput“omics” technologies enable the generation of large-scale data sets from genetics, transcriptomics, proteomics, epigenetics, microbiome to metabolomics and intensive knowledge of how each layer relates to diseases. Combined with clinical data, we now have an opportunity to construct a holographic view for a medical problem using in silico computational models. And the release of global metabolic network (current version, Recon3), entitles us a great starting point for the goal of PM.

Our lab is interested in:

Simulating the metabolism of specific cell or tissue type using genetic, transcriptomic, proteomic and metabolomic data etc. For example, metabolic modeling of muscle of patients after Injury;

Developing faster tools and algorithms for large scale simulations;

In silico modeling of pathogen and the host response for better treatments.

Whole body model of human metabolism.

Dr. Feifei Han and Dr. Gonghua Li are in charge of this project.