Biosciences researchers collaborated with a team at the Salk Institute that developed a computational algorithm that integrates two different data types to make locating key regions within the genome more precise and accurate than other tools. The team’s method, recently described in Proceedings of the National Academy of Sciences, could help researchers conduct vastly more targeted searches for disease-causing genetic variants in the human genome, such as ones that promote cancer or cause metabolic disorders. Joseph Ecker, a Howard Hughes Medical Institute investigator and director of Salk’s Genomic Analysis Laboratory, was senior author of the study. Diane Dickel, Axel Visel, and Len Pennacchio of the Environmental Genomics & Systems Biology Division, were co-authors, along with other researchers at the Salk Institute, UC San Diego, and UC San Francisco. Read more about the study in the Salk Institute press release.
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