Areas of Research
Functional study of cells and their interactions.
Dr. Jean Pierre Etchegaray: DNA oxidations as epigenetic elements regulating cell fate identity. Transcriptional mechanisms triggering cancer initiation. Circadian rhythms and cancer-stem cells.
Dr. Nan Gao: Molecular events that control and/or disrupt mitotic cell division and epithelial polarity in mammalian development and disease.
The study of the structure and functions of individual neurons.
Dr. Radek Dobrowolski: Molecular mechanisms leading to neuronal death as observed in Alzheimer’s and Parkinson’s disease.
Dr. Wilma Friedman: Cellular mechanisms of neurotrophin actions on CNS neurons and glia during brain development and after injury.
Dr. Haesun Kim: Cellular and molecular biology of myelinating glial cells: Mechanism of signal transduction involved in axon-Schwann cell interaction. Molecular mechanism of cell fate determination in the developing peripheral nervous system.
Dr. Tracy S. Tran: The Tran lab investigates the cellular and molecular mechanisms of axonal guidance, dendritic morphogenesis and neural circuit formation. Our research aims to understand the molecular signaling involved in how neurons assume their diverse morphologies, the axons and dendrites, which enable the assembly of neural circuits required for complex behavior and cognitive function. The Tran lab is also interested to better understand and identify the molecular and genetic correlates of autism spectrum disorder.
Dr. Ching-On Wong: Organellar biology, cell metabolism and bioenergetics in the contexts of nervous system function and neurodegenerative diseases. Major emphasis on how vesicular trafficking and inter-organellar signaling regulate and react to metabolic outputs and demands of neurons and glia.
Dr. Rola Bektesh
Dr. Susan Seipel
Dr. Miguel Cervantes Cervantes
Dr. Megan McSherry Hill
Dr. Caroline Maier
Areas of Research
Interactions and dynamics of organisms and their environment.
The patterns and processes responsible for generating biodiversity.
Working to understand the properties and behavior of neural networks.