Research Abstracts Online
2008 - March 2009
University of Minnesota Twin Cities
Institute of Technology
Department of Electrical and Computer Engineering
PI: Guillermo R. Sapiro
Co-PI: Christophe Lenglet
Statistical Characterization of Protein Ensembles; Computational and Mathematical Techniques for Diffusion MRI Processing
In one project during this period, these researchers investigated protein ensembles. When structural fluctuations or measurement errors should be accounted for, a single rigid structure may not be enough to represent a protein. One approach to solving this problem is to represent the possible conformations as a discrete set of observed conformations (ensemble). Following a different approach, these researchers are introducing a framework for estimating probability density functions in very high dimensions and applying it to represent ensembles of folded proteins.
In another project, the researchers are developing new mathematical and computational models for processing diffusion magnetic resonance imaging, a recent non-invasive technique providing connectivity information in the brain. This powerful imaging modality has opened up a landscape of exciting discoveries for medicine and neuroscience and the tools the group is developing will result in fundamental advancements for research on pathological brain degeneration such as stroke, Alzheimer’s disease, or neuropsychiatric disorders like schizophrenia. This is a challenging task that requires both advanced mathematical models and high-performance computing capabilities.
Iman Aganj, Graduate Student
Diego Rother, Graduate Student