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Research
Projects
ODU's existing strengths in bioinformatics
include faculty members in various departments (Computer
Science, Mathematics and Statistics, Chemistry,
Oceanography, in addition to Biology) who are already
doing research in the area.
Chris
Osgood, Alex Pothen, Dayanand Naik and collaborators at
EVMS (Eastern Virgina Medical School) are exploring how
changes in gene expression levels can help characterize
cancers. One group working in microbial genomics
consists of Andrew Gordon, Wayne Hynes, Dan Sonenshine,
Fred Dobbs and collaborators at EVMS.
A
group of quantitative ecologists consisting of Cynthia
Jones, Mark Butler, and Bill Ressetaris are interested
in exploring the new field of environmental informatics.
Kent
Carpenter and Tamas Burke (at EVMS) are studying
phylogenetic relationships of fishes and viruses.
Jennifer
Radkiewicz, Michael Wagner, Glenn Williams are exploring
various aspects of the protein folding, molecular
dynamics of enzyme catalysis, and three dimensional
geometry of proteins.
Alex
Pothen is interested in computational representations of
protein interaction networks and
multi-protein complexes. Mohammaed Zubair and Kurt Maly
are creating frameworks in XML and BioML for web
technologies so that heterogeneous data from biological
experiments (sequences, mass spectra, NMR, etc.) can be
processed by bioinformatics programs without human
intervention.
Projects
Computational
Proteomics: Algorithms for Classifying Prostate Cancer
Dayanand
Naik, Alex Pothen, Michael Wagner, Srinivas Kasukurti,
Raghuram Devineni
Objective
: One of the goals of proteomics is to develop fast,
automatable, and inexpensive techniques to identify
proteins from mixtures, to match the recent developments
in genomics. One of the novel technologies for
accomplishing this is called Surface Enhanced Laser
Dissociation Ionization (SELDI) mass spectrometry. We
are collaborating with Prof. Wright's group (at Eastern
Virginia Medical School) in analyzing
protein mass spectral data obtained from SELDI on serum
and prostate fluid samples. The goal is to make use of
the protein signatures from mass spectra to classify
patient samples into healthy, early prostate cancer,
late prostate cancer, and benign prostate hyperplasia (BPH).
Statistical analysis of microarray
data
Prof.
Rao Chaganty
Computational
Problems in Statistical Genetics
Prof.
Rao Chaganty
Genomic mapping of astrovirus
VPg
Badr Al-Mutairy, Jolan Walter (EVMS), Alex
Pothen
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