Yves A. Lussier

This paper develops a framework combining paired-sample dynamics, pathway-based analytics, and MLOps to improve transcriptomic classification in small cohorts, achieving high precision and recall in case studies.

The paper evaluates MPSE's performance in prioritizing NICU newborns for WGS within 48 hours using various ML classifiers, CNLP tools, and data types, finding high accuracy and flexibility.

The paper introduces Inter-N-of-1, a method to detect biomechanism differences in small cohorts by analyzing single-subject transcriptome data, showing high precision and recall in simulations and a clinical dataset.

binomialRF identifies biomarkers and their interactions using a scalable random forest approach with statistical hypothesis testing for feature selection.

The paper evaluates single-subject methods for differential gene expression analysis and finds ensemble methods perform best in identifying DEGs without replicates.

The paper introduces iDEG, a method to identify differentially expressed genes in a single subject without replicates, showing improved accuracy over existing methods in simulations.