Author

Thomas Laurent

Loyola Marymount UniversityPrimary ORCID profile (0000-0001-6729-4419 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Thomas LaurentiD1 paper · Inserm

Biology Disciplines

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Bioinformatics· 1

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Approach:deep learning· 1 Research Focus:genome assembly· 1 Organism:human· 1 Organism:mouse· 1 Organism:rat· 1 Assay:whole-genome sequencing· 1

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Kenji KawaguchiiD· 1 shared Lovro VrčekiD· 1 shared Martin SchmitziD· 1 shared Mile ŠikićiD· 1 shared Xavier BressoniD· 1 shared

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2025-2025 · peak 1/yr

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1 shared paperBioinformatics

Kenji KawaguchiORCID

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1 paper

Recent·Most cited

Geometric deep learning framework for de novo genome assembly

Lovro Vrček, Xavier Bresson, Thomas Laurent, Martin Schmitz, Kenji Kawaguchi, Mile Šikić

This paper introduces GNNome, a geometric deep learning framework for de novo genome assembly that improves contiguity compared to existing tools across multiple species.

Genome Research · Apr 1, 2025Peer-reviewedBioinformatics