Genomics of gene regulation: we seek to achieve a global understanding of the genomic basis of gene regulation, particularly over time and in development, using functional genomics and machine learning. We have a long standing interest in identification of cis-regulatory modules, particularly long-range enhancers. More recently, we have been focusing on understanding the determinants of 3D genome organization and its role in gene regulation.
Data intensive science: We work to increase access to compute and data intensive methods for the scientific research community, particularly in genomics. We are part of the team that develops Galaxy, a framework for making large scale computational analysis more accessible and reproducible. In the context of Galaxy we have research interests in data visualization and analytics, cloud and high-performance computing, transparent and reproducible scientific publication. We are particularly concerned with improving the reproducibility of published scientific results that depend on complex methods.
Genome-wide comparative analysis reveals human-mouse regulatory landscape and evolution – Our comprehensive analysis of exaptation of regulatory elements is now published in BMC Genomics.
Being a part of the open source community – means participating and contributing to Sprints, Hackathons and Codefests - a process now captured in a paper.
Mouse ENCODE Consortium Papers out – comprehensive mapping and comparison of functional genomic data in human and mouse.
Two articles at Supercomputing 2014 – were published (1) describing a Galaxy federation model and (2) providing an overview of the current Big Data analysis tools.
Welcome Enis Afgan to the lab – Enis Afgan, cloud and distributed computing expert, had joined the lab as an Associate Research Scientist as of July 2014.