The goal of this project is to use data integration and network analyses to discover disease mechanisms and potential treatments.
Disease knowledge-based networks reflect the current understanding of diseases between clinical phenotypes/symptoms, drugs, genotypes and other molecular interactions.
By applying network of biomedical knowledge to integrate clinical phenotypes and molecular signatures of ME/CFS, we hope to uncover disease gene modules and to prioritize drug candidates for repurposing to help disease symptoms and progression.
Knowledge-Based Network Medicine
Systems Biology Modeling of Metabolic Dysfunctions
We developed systems-level metabolic models for viral infected human tissues to understand viral induced metabolic dysfunctions and to identify potential novel treatments.
In collaboration with clinicians at MGH, we identified candidates of autoimmunity for further investigation.
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