We are involved with several projects and consortia related to my research areas.
The Type 2 Diabetes Knowledge Portal (T2DKP)
We implement the data coordinating center (DCC) for the Type 2 Diabetes Knowledge Portal (T2DKP), funded by the Accelerating Medicines Partnership for Type 2 Diabetes (AMP-T2D). We develop methods, analysis platforms, and software to make T2D-relevant genomic data broadly and publicly accessible, to accelerate its use in biological and therapeutic discovery.
T2D-GENES, GoT2D, and DIAGRAM
We are involved in several consortia whose aim is to identify, through collaborative genetic analyses, loci, genes, and variants associated with T2D. In particular, the T2D-GENES consortium published an analysis of multi-ethnic exome sequence data in 12,940 samples, with ongoing analyses of sample sizes now exceeding 55,000, and the GoT2D consortium published an analysis of whole-genome sequence data in 2,647
The biomedical data translator program
We are a part of the Broad Institute investigative team on the NCATS biomedical translator feasibility study. The goal of the translator project is to pilot techniques for mapping data types and concepts between clinical and biological research settings; our group is prototyping the use of probabilistic graphical models to represent a range of biomedical entities and data types.
Platform for accelerating genetic discovery for cerebrovascular disease
Our team has extended our software for the T2DKP to apply to other disease areas as well. This includes a knowledgebase and portal for stroke genetics, housing data from the International Stroke Genetics Consortium.
We have previously worked on Graemlin, an algorithm for comparing large-scale protein interaction networks. We produced three versions of Graemlin: a heuristic algorithm designed to scale for the first time to multiple dense networks, a machine learning algorithm for increasing accuracy of global network alignment, and an extension of this machine learning algorithm to local network alignment.