Using deep learning and artificial intelligence to map the genome and predict disease

Featured in MedCity News, July 22, 2015.

Deep Genomics, a fresh new University of Toronto spinout, is combining deep machine learning techniques with artificial intelligence to study the human genome. It’s building out a database in which a user can type in a combination of mutations found in a patient – and it’ll spin out the likelihood and severity of a patient getting a disease.

“We use machine learning to try to mimic the way in which the cell works – and predict whether a person will get a disease or not,” CEO Brendan Frey said in a phone interview. And he describes it as “something akin to a Google search engine for genomics.”

This could make Deep Genomics a tantalizing new player in precision medicine.

We already have a searchable database of mutations, but what makes Deep Genomics’ approach unique is that it’s opening up a genome-wide database of more than 300 million potentially disease-causing variants, “most of which are in regions of the genome that can’t be examined using other methods,” Frey said. [...]