Biological cells are complex dynamic systems that exhibit both extreme robustness and fragility. Robustness can be characterized as a cell's ability to isolate perturbations locally, which is a useful feature in the context of drug discovery, as treatments need to be efficacious with minimal adverse side effects. On the other hand, cells also possess fragile points that can stimulate apoptoic (cell death) pathways, providing intuitive targets for anti-cancer therapy. My overall goal is to develop a strong engineering research platform to study these two system properties at a fundamental level and ultimately facilitate the discovery of novel drug targets in diseased mammalian cells. My research involves the integration of large-scale omics data with metabolic and signaling networks to quantify cellular dynamics in response to various stimuli. In particular, I plan to develop state-of-the-art experimental workflows for efficient metabolomics and proteomics data collection using LC/MS-MS (liquid chromatography-mass spectrometry). I also have a strong interest in applying ‘Big Data Analytics' and parallel cloud computing for systems biology applications to ensure that the algorithms we develop are scalable with the increasing complexity of biological networks. As a primary application of my work, I plan to explore novel treatments for liver disease, specifically nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (liver cancer).
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