Author

Lennert Verboven

University of AntwerpORCID 0000-0002-5647-5852Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:drug response / drug discovery· 1 Research Focus:phylogenetics / evolution· 1

Frequent Co-Authors

Annelies Van RieiD· 2 shared Robin M. WarreniD· 2 shared Tim H. HeupinkiD· 2 shared Abhinav SharmaiD· 1 shared Miguel de Diego Fuertes· 1 shared Vincent RennieiD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Annelies Van RieORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintOct 4, 2023

The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples

Tim H. Heupink, Lennert Verboven, Abhinav Sharma…·Annelies Van Rie

The MAGMA pipeline improves variant calling and drug resistance analysis for Mycobacterium tuberculosis samples with low coverage and high contamination.

2 citations

whole-genome sequencingmachine learning (classical)

𝕏 PostBluesky

GenomicsMicrobial GenomicsPeer-reviewedNov 18, 2021

Comprehensive and accurate genetic variant identification from contaminated and low coverage Mycobacterium tuberculosis whole genome sequencing data.

Tim H. Heupink, Lennert Verboven, Robin M. Warren, Annelies Van Rie

This paper introduces XBS, a bioinformatics pipeline that improves variant detection in contaminated and low coverage Mycobacterium tuberculosis sequencing data, outperforming existing methods in complex genomic regions and low-depth samples.

20 citations

whole-genome sequencingmachine learning (classical)

𝕏 PostBluesky