Our lab focuses on designing algorithms to gain biological insights from advances in automated data collection and the subsequent large data sets drawn from them.
We work on a diverse set of problems, including compressive genomics, network inference, structural bioinformatics, genomic privacy, and medical genomics.
We aim to develop a context-aware data-driven functional genomics framework that can characterize tissue-specific gene representations, provide context-aware genotype to phenotype mapping, and enable network-based exploration of disease genetics.
Genome-wide association studies, which look for links between particular genetic variants and incidence of disease, are the basis of much modern biomedical research.
