742 citations · 806 across the 9 of their papers we have counts for
4 papers · 1 filter
Large scale modeling of antimicrobial resistance with interpretable classifiers
Alexandre Drouin, Frédéric Raymond, Gaël Letarte St-Pierre +3
Antimicrobial resistance is an important public health concern that has implications in the practice of medicine worldwide. Accurately predicting resistance phenotypes from genome…
Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance
Alexandre Drouin, Sébastien Giguère, Maxime Déraspe +3
The Set Covering Machine (SCM) is a greedy learning algorithm that produces sparse classifiers. We extend the SCM for datasets that contain a huge number of features. The whole gen…
Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine
Alexandre Drouin, Sébastien Giguère, Vladana Sagatovich +4
The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes…
Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species
Keith R. Bradnam, Joseph N. Fass, Anton Alexandrov +88
Background - The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished g…