Sébastien Lemieux

Published on May 10, 2019

Sequencing of the 20,000 human genes produced countless data that must now be deciphered in order to give it meaning. Bioinformatician Sébastien Lemieux, of the Institute for Research in Immunology and Cancer of the Université de Montréal, devotes himself to that task in the field of cancer research.

“We use artificial intelligence to analyze data” he said during an interview. Using samples taken from 482 patients suffering from a form of cancer, acute myeloid leukemia, he is currently trying to determine the genetic profile of the cancer cells. “We are still a long way from a clinical application of the tools that we are developing, where artificial intelligence and genetics converge, but we hope to better understand the genetic composition of the disease” he explained.

Over time, researchers could perfect tools that would assist clinicians with their therapeutic choices. Just a few short years ago, we couldn’t attend to that task without a huge budget, as the analysis of each sample could cost as much as $2,000. The giant step taken over the last 20 years has made certain analyses much more accessible. Existing instruments are very effective, points out Professor Lemieux, who studied microbiology prior to specializing in computer science. Given the number of genes involved (still undetermined, but which could be high), the Investigator uses artificial intelligence algorithms to allow computers, to some extent, to teach themselves how to explore the genome, looking for early warning signs of the disease. “It’s called deep learning. It’s one of the specialties of the Université de Montréal’s team under the supervision of Yoshua Bengio” he added.

In a recently launched research project bringing together several UdeM professors including Guy Sauvageau, Joseph Paul Cohen and Yoshua Bengio, Professor Lemieux hopes to “study rare subgroups of acute myeloid leukemia and more subtle biological mechanisms involved”. He feels that the project will lead to “new observations that will have real influence on our understanding of the disease”.