Biological search engine

It may take weeks for a biologist to comb through a stack of journal articles and discover that one gene is functionally related to another. This relationship could lead to a new way to fight a disease - but not if it remains hidden.

Berkeley Lab researchers hope to accelerate this needle-in-a-haystack hunt with an innovative search engine that simulates the way scientists think. It’s called GenoPharm, and rather than search through data by keyword, the way Google does, it searches by association, like scientists do.

“GenoPharm mimics the way biologists search through biomedical literature for connections between genes,” says Kasian Franks of Berkeley Lab’s Life Sciences Division, who developed the software with Life Sciences biologists Mina Bissell and Connie Myers. “It could enable a biologist to do in minutes what now takes them days.”

To use GenoPharm, a person enters a gene symbol and selects a context, such as “molecular function” or “therapeutics.” The result is a web of relationships, with genes that appear more closely together in scientific literature appearing more closely together in the web. Plug in “BRAC-1,” for example, which is a gene that plays a role in breast cancer, and a GenoPharm search yields a sprawling network of associations.