Assistant Professor Gaurav Chopra’s research group works in the area of chemical data science and machine learning for analytical, physical and biological chemistry applications. His lab integrates data science, molecular modeling, machine learning for analytical chemistry and chemical biology applications. They combine data from specific biological and functional experiments done in his laboratory on immune cells of interest to discover drugs and synthesize chemical probes for the treatment and diagnosis of neurological diseases and cancers. His lab discovers “chemical rules” from small and large datasets of experimental structures, spectral data from analytical instruments to identify chemical features (Figure 5), integrates biological experiments and chemical reaction conditions with systems-based modeling of chemical reactivity to guide biological and synthetic experiments. Several software modules for CPU, GPU (graphical processing unit) on cheminformatics, chemical/structural modeling, machine learning methods for identifying chemical features based on statistical data integration, molecular simulation have been developed by his laboratory (see chopralab on GitHub).
REU students in the Chopra laboratory will have the opportunity to work on projects in the areas of computational chemical/biological modeling, machine learning, statistical methods for experimental data integration, doing chemical synthesis of small molecules/probes, chemical conjugation of live cells to functionalize cells as sensors and drug delivery agents, and biological validation of molecules and probes on cell-based assays. Each REU student will be working with either a senior graduate students (Jonathan Fine, Priya Prakash, Armen Beck, Ahad Hossain) or a postdoctoral scholar (Dr. Krupal Jethava) including weekly meetings with Gaurav Chopra.