Author

Mathieu Quenu

Centre National de la Recherche ScientifiqueORCID 0000-0001-9392-6360Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:plant (other)· 2 Research Focus:cell type annotation· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1 Research Focus:genome assembly· 1 Approach:machine learning (classical)· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Antoine ClaessensiD· 2 shared Alex MakuniniD· 1 shared Camille CoheniD· 1 shared Elcid Aaron PangilinaniD· 1 shared Godfrey Kinyori Wagutu· 1 shared Mara LawniczakiD· 1 shared Marc-Antoine GueryiD· 1 shared Prince NyarkoiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersGenomics

Antoine ClaessensORCID

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2 papers

Recent·Most cited

GenomicsG3 Genes Genomes GeneticsPeer-reviewedOct 27, 2026

De novo assembly of complete Plasmodium falciparum isolate genomes using PacBio HiFi sequencing technology

Prince Nyarko, Mathieu Quenu, Marc-Antoine Guery…·Antoine Claessens

This study uses PacBio HiFi sequencing to assemble complete Plasmodium falciparum genomes from natural infections, revealing full repertoires of immune-related genes.

2 citationstop 3%

plant (other)whole-genome sequencing

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BioinformaticsbioRxivPreprintMay 19, 2025

upsAI: A high-accuracy machine learning classifier for predicting Plasmodium falciparum var gene upstream groups

Elcid Aaron Pangilinan, Mathieu Quenu, Antoine Claessens, Thomas D. Otto

The paper introduces upsAI, a machine learning classifier that accurately predicts Plasmodium falciparum var gene upstream groups from partial sequences, achieving high accuracy compared to existing tools.

1 citation

plant (other)DNA methylation

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