Bioinfomatics
Design and construction of algorithms and software systems for analysis of biological sequence data, including genomic DNA sequences, expressed DNA sequences, and protein sequences. Research also includes the theory of algorithms and its applications to biological computing and developing clustering and classification techniques for genomic sequences and computer aided diagnosis (CAD) of neurodegenerative diseases using high resolution structural Magnetic Resonance Images (MRI). Research Labs/Areas
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Advanced Laboratory for Information Systems and Analysis (ALISA) - Lead Faculty: Professor Acharya ALISA members investigate novel approaches to
manage and analyze biomedical informatics data including patient
demographics, clinical data, gene expression data generated from DNA
microarrays, and integrate these approaches to pharmaceutical research. Computational Biology Laboratory - Lead Faculty: Professor Berman
Professor Berman is working on theoretical issues of distributed
systems and approximation algorithms. In general, he is interested in
the theory of algorithms and its applications to biological computing.
Center for Comparative Genomics and Bioinformatics (CCGB) - Co-Director: Professor Miller
Professor Miller's lab is part of the CCGB, which brings together
collaborators from the computer science and engineering, biochemistry
and molecular biology, biology, and statistics departments. The lab
works in the general area of computational molecular biology, with
particular focus on the development of algorithms and software for
comparing genome-long mammalian DNA sequences. Current projects include
ancestral genome reconstruction and sequencing of Mammoth DNA.
Laboratory for Biomedical Image Analysis (LBIA) - Director: Professor Liu
The mission of the LBIA is to fully exploit the computational power of
state-of-the-art computer vision technology and computer hardware,
side-by-side with physicians, in automatic discovery of the most
discriminative feature subspaces for computer-aided diagnosis (CAD) and
early detection of neurodegenerative diseases from multimodal,
multidimensional clinical data and longitudinal research data including
structural and functional magnetic resonance images (MRI), positron
emission tomography (PET) and genetic variations and neurobiological
markers. We develop advanced machine-learning based computer algorithms
for deformable biomedical image registration, segmentation, novel and
massive feature extraction, including 3D deformation and tensor fields,
and quantified asymmetry measures of human brains. Our present focus of
types of neurodegenerative diseases are Alzheimer's disease, autism,
and schizophrenia. Currently, Professor Liu is leading an effort on
early detection of mild cognitive impairment (MCI), emerging as a
concept of a prodromal form of AD, using longitudinal high resolution
MR images (a recent report of the AD project can be found at: www.thetartan.org/2006/02/13/scitech/research profiles).
Bioinformatics Data Mining Laboratory - Lead Faculty: Professor Li Professor Li's research interests in the area of bioinformatics involve developing clustering and classification techniques for genomic sequences. |
