This collaborative, multi-disciplinary project will exploit recent progress in genomics - the study of the complete genetic content of species and how it works - to greatly advance our knowledge of evolutionary relationships in the insect order Lepidoptera (moths and butterflies). A broad-scale "family tree" (phylogeny, genealogy) will be estimated using DNA sequences from approximately 250 species, representing all 126 families into which Lepidoptera are currently divided.

Rapid advances in DNA sequencing technologies are providing scientists with the ability to rapidly and cost-effectively decode the genomes of organisms. Current technologies, however, can only reconstruct a fragmented picture of a genome's chromosomes. Stitching the resulting fragments together into a complete genome currently requires costly and time-intensive laboratory experiments.

The University of Maryland College Park is awarded a grant to develop new algorithms and a suite of software tools based on a general and flexible definition of a ""network module"" in order to extract meaningful biological clusters from noisy and incomplete protein-protein interaction data. Recently developed high-throughput techniques are being used to sample protein-protein interactions from many organisms and are creating a wealth of data that must be analyzed computationally.

New generation DNA sequencing technologies are revolutionizing modern biological research. Scientists can now generate the rough equivalent of an entire human genome (~3 billion base-pairs of DNA) in just a few days with one single sequencing instrument. Until recently, such amounts of data could only be generated at large genome centers using hundreds of sequencers. The analysis of these data is complicated by their size - a single run of a sequencing instrument yields terabytes of information, often requiring a significant scale-up of the existing computational infrastructure.