June 9, 2014
FOR IMMEDIATE RELEASE
CONTACT: Phil Sneiderman
Benjamin Langmead, assistant professor in the Department of Computer Science at Johns Hopkins University’s Whiting School of Engineering, has been chosen by the National Science Foundation to receive its prestigious CAREER Award, which recognizes the high level of promise and excellence in early-stage scholars.
The five-year grant will support Langmead’s work developing improved computational and statistical methods for analyzing DNA sequencing data. His goal is to provide faster, more accurate, and more interpretable results to scientists studying organisms with repetitive genomes. Earlier this year, he was selected as a 2014 Alfred P. Sloan Research Fellow in Computational & Molecular Biology for his work in a related area.
“Many genomes, including the human genome, have been invaded by foreign bits of DNA that are able to copy and paste themselves throughout the genome,” Langmead said. “When we sequence the genome, these ‘repetitive elements’ are a major hindrance — they make our algorithms slower and less accurate. This award allows us to pursue new methods for reconstructing repetitive genomes from sequencing data quickly and accurately. We are very grateful to the National Science Foundation for this support.”
Gregory D. Hager, professor and chair of the Department of Computer Science, said, “Ben’s work has been revolutionary in computational biology. His work on sequence alignment, in the form of the Bowtie software, is already used worldwide. Having him at Johns Hopkins adds to our ‘unfair advantage’ in computational genomics, where we now have one of the leading groups in the country.”
Langmead’s research focuses on ways of making high-throughput data easier to analyze and interpret. He uses approaches from computer science and statistics to create high-impact software tools widely used in genomics research and by other scientists. He earned his bachelor’s degree in computer science from Columbia University and his master’s and Ph.D. degrees in computer science from the University of Maryland College Park.