Our research group aims to further our understanding of the human genome by developing computational and statistical methods to analyze large genomic datasets. Our main areas of interest are regulation of gene transcription, chromatin state/accessibility, gene-environment interactions, and genetics of complex traits. Our goal is to characterize the regulatory grammar encoded in the DNA sequence and the impact of genetic variants and environmental changes in determining gene expression levels. We hope that the methods and resources developed will help us determine the molecular mechanisms leading to variation in complex traits and genome evolution.
In our work we use techniques form different backgrounds such as signal processing, statistical modeling, machine learning and computer science. These techniques have been very useful in developing novel computational methods for extracting biologically relevant information from large genomic datasets.
Our current main projects are:
– Predicting Genetic Variants Affecting Gene Regulation
– Genetic and Environmental Determinants of Complex Traits
– Condition Specific Transcription Factor Binding Footprints