Johns Hopkins researchers have succeeded in teaching computers how to identify commonalities in DNA sequences known to regulate gene activity, and to then use those commonalities to predict other regulatory regions throughout the genome. The tool is expected to help scientists better understand disease risk and cell development.
The work was reported in two recent papers in Genome Research, published online on July 3 and Sept. 27.
“Our goal is to understand how regulatory information is encrypted and to learn which sequence variations contribute to medical risks,” says Andrew McCallion, Ph.D., associate professor of molecular and comparative pathobiology in the McKusick-Nathans Institute of Genetic Medicine at Hopkins. “We give data to a computer and ‘teach it’ to distinguish between data that has no biological value versus data that has this or that biological value. It then establishes a set of rules, which allows it to look at new sets of data and apply what it learned. We’re basically sending our computers to school.”