Author

Rébecca Panès

Institute for Research in Immunology and CancerORCID 0000-0002-2180-0416Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Organism:mouse· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Albert FeghalyiD· 1 shared Claude PerreaultiD· 1 shared Étienne GagnoniD· 1 shared François MajoriD· 1 shared Lea A. HarringtoniD· 1 shared Mathieu CourcellesiD· 1 shared Maude Dumont-LagacéiD· 1 shared Mohamed BenhammadiiD· 1 shared

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2020-2020 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Albert FeghalyORCID

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1 paper

Recent·Most cited

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation

Tariq Daouda, Maude Dumont-Lagacé, Albert Feghaly, Yahya Benslimane, Rébecca Panès, Mathieu Courcelles, Mohamed Benhammadi, Lea A. Harrington, Pierre Thibault, François Major, Yoshua Bengio, Étienne Gagnon, Sébastien Lemieux, Claude Perreault

The paper introduces CAMAP, an artificial neural network that predicts MHC-I peptide presentation by analyzing codon arrangement in mRNA sequences, improving prediction accuracy beyond traditional methods.

bioRxiv · Jun 3, 2020 · PreprintBioinformatics