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The Langmead Lab is seeking a postdoctoral fellow in 2016 to join our research program. See the open positions page for details.

High-throughput life science instruments, especially DNA sequencers, are improving very rapidly. A DNA sequencer is now capable of generating enough data to cover the human genome dozens of times over in approximately one week. Sequencing has become a ubiquitous tool in the study of biology, genetics and disease. Today, because sequencing throughput is outpacing computer speed and storage capacity, the most crucial biological research bottlenecks are increasingly computational: computing, storage, labor, and power.

The laboratory’s goal is to make high-throughput life science data as useful as possible to everyday life scientists. We pursue this goal by:

  1. Developing methods and software tools that are efficient, allowing researchers to interact with datasets quickly and effectively. See: BowtieBowtie 2, Lighter, Arioc, HISAT.
  2. Developing scalable tools that allow researchers to work with very large datasets, or large collections of datasets. See: Rail-RNA, Myrna, CrossbowReCount, Intropolis, Boiler.
  3. Making output from our software as interpretable as possible, meaning that when a life scientist looks at a result, he or she should be able to understand what conclusion was reached, why it was reached, and what degree of confidence to have in it.

The lab uses approaches from computer science — algorithms, text indexing, and high performance computing, especially cloud computing — and from statistics to create high-impact software tools (see sidebar) benefiting the wide community of life scientists who rely on these data for their research.

The lab is located at the Johns Hopkins University Department of Computer Science.