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.
Charbel Machaalani and Eve Wang presented their work at the 5th IRIC Summer Interns' Day. They jointly won the prize for best poster presentation for their posters: “Implementation of neural networks to predict gene expression using compound structures” by Eve Wang and “Implementation of a new neural network approach to characterize small molecules for drug development using gene profiles” by Charbel Machaalani.
Maria Virginia Ruiz Cuevas’s article, “BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens”, has been published in BMC Genome Biology and is now publicly available online. Congratulations, Maria!
Congratulations to Dr. Maria Virginia Ruiz Cuevas for a successful thesis defense! Her thesis, titled “Improving anti-cancer therapies through a better Identification and characterization of non-canonical MHC-I associated peptides”, will be available shortly on the UdeM’s Papyrus system.
Carl Munoz and Leonard Sauve have been invited to present their ongoing work as posters at GLBIO 2023, an ISCB conference. Leaonard Sauve’s poster, entitled “Factorized Embeddings demonstrate that transcriptomic profiles can be summarized into very few genetic components useful for sample-related and biological feature detection”, and Carl Munoz’s poster, entitled “C-less is K-more: k-mers as an alternative to gene expression in low-coverage RNA-seq”, will be made available at a later time.
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).