Bioinformatics & Cancer Research
Our lab is affiliated to the Institute for Research in Immunology and Cancer (IRIC) at the Université de Montréal (UdeM). Our multidisciplinary team develops bioinformatics tools and analysis pipelines, and leverages machine learning and other computational approaches to analyze omics data such as transcriptomic, chemogenomic, and proteomic data. Through fundamental, translational and clinical research, we help improve cancer treatment.
What’s new
Jeremie Zumer’s abstract: Pepid: a Highly Modifiable, ML-Friendly Peptide-Centric Search Engine, introducing the Lemieux Lab’s Pepid search engine, has been accepted for a poster presentation at the Machine Learning and Computational Biology conference (MLCB 2022). The poster can be downloaded by following this link (1.3MB).
Leonard Sauve presents his visualization method for transcriptomic data in accute myeloid leukemias (AML) using the Factorized Embedding model at ReseauxLAB 2022. The Factorized Embedding model was first developed by Assya Trofimov during her doctoral studies in the Lemieux lab. The poster can be viewed or downloaded by following this link (2.08MB).
Caroline Labelle’s presentation: Bayesian Inference as a Robust Alternative to Non-Linear Regression for Dose-Response Parameters Assessment, has been accepted at the 2022 edition of the International Conference on Intelligent Systems for Molecular Biology (ISMB). The poster abstract can be found online.