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Biomolecular informatics; molecular structure-function modeling using statistical and machine learning approaches

Institution: University of North Carolina Eshelman School of Pharmacy

Website: http://pharmacy.unc.edu/Directory/tropsha

Email: alex_tropsha@unc.edu

Voice: (919) 966-2955

Publications

The major area of our research is Biomolecular Informatics, which implies understanding relationships between molecular structures (organic or macromolecular) and their properties (activity or function). We are interested in building validated and predictive quantitative models that relate molecular structure and its biological function using statistical and machine learning approaches. We exploit these models to make verifiable predictions about putative function of untested molecules.