Sequence Analysis and Modeling Lab
Discriminative Graphical Models
In Collaboration with Dr. James M. Rehg and Yushi Jing, College of Computing, Georgia Institute of Technology.
Discriminative learning, or learning for classification, is a common learning task that has been addressed in a number of different … Read the rest
The brain mechanisms underlying the ability of humans to process faces have been studied extensively in the last two decades. Brain imaging techniques, particularly fMRI (functional Magnetic Resonance Imaging) that possesses high spatial resolution but limited temporal resolution, are advancing … Read the rest
Protein Classification and Functional Prediction
Problem
Proteins are linear seqeuences of amino acids that perform essential functions in organisms. To determine the function of a protein, expensive experimental procedures are required. With better sequencing techniques, it becomes evident that computational … Read the rest
Kernel Methods for Sequence Classification
DNA Barcoding
Genomic approaches to classification of organisms exploit diversity among DNA sequences to identify organisms. The task of identification is to assign any unidentified organism to the taxonomic group at the target level: class, … Read the rest
Fast Semi-Supervised Homology Prediction using Sparse Spatial Sample Kernel
Motivation:
Establishing structural and/or functional relationship between sequences, for instance, to infer the structural class of an unannotated protein, is a key task in a biological sequence analysis. Recent methods such … Read the rest