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

Advanced Laboratory for Information Systems and Analysis (ALISA) �¯�¿�½ 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 �¯�¿�½ 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) �¯�¿�½ 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) �¯�¿�½ 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 �¯�¿�½ Lead Faculty: Professor Li

Professor Li's research interests in the area of bioinformatics involve developing clustering and classification techniques for genomic sequences.