School of Medicine
Showing 1-20 of 127 Results
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Axel Brunger
Professor of Molecular and Cellular Physiology, of Neurology, of Photon Science and, by courtesy, of Structural Biology
Current Research and Scholarly InterestsOne of Axel Brunger's major goals is to decipher the molecular mechanisms of synaptic neurotransmitter release by conducting imaging and single-molecule/particle reconstitution experiments, combined with near-atomic resolution structural studies of the synaptic vesicle fusion machinery.
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Steven Chu
William R. Kenan Jr. Professor and Professor of Molecular and Cellular Physiology
Current Research and Scholarly InterestsSynthesis, functionalization and applications of nanoparticle bioprobes for molecular cellular in vivo imaging in biology and biomedicine. Linear and nonlinear difference frequency mixing ultrasound imaging. Lithium metal-sulfur batteries, new approaches to electrochemical splitting of water. CO2 reduction, lithium extraction from salt water
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Aleksandra Chudinova
Postdoctoral Scholar, Molecular and Cellular Physiology
Current Research and Scholarly InterestsI am part of the wormsense lab where we study the molecular and biophysical mechanisms endowing sensory neurons with the capacity to perceive mechanical and thermal stimuli. I study the mechanisms involved in the regulation of degeneration and regeneration of sensory endings. Using genetics, in vivo imaging, electrophysiology and behavioral assays in C.elegans I screen for small molecules that restore touch sensation following chemotherapy and I validate their therapeutic potential in mice.
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Ron Dror
Associate Professor of Computer Science and, by courtesy, of Molecular and Cellular Physiology and of Structural Biology
Current Research and Scholarly InterestsMy lab’s research focuses on computational biology, with an emphasis on 3D molecular structure. We combine two approaches: (1) Bottom-up: given the basic physics governing atomic interactions, use simulations to predict molecular behavior; (2) Top-down: given experimental data, use machine learning to predict molecular structures and properties. We collaborate closely with experimentalists and apply our methods to the discovery of safer, more effective drugs.
