Author

Dennis Hendriksen

University Medical Center GroningenORCID 0000-0003-0417-625XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2

Signature Assays, Organisms & Methods

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Research Focus:variant effect prediction· 2 Assay:whole-exome sequencing· 2 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Bart CharboniD· 2 shared Birgit Sikkema‐RaddatziD· 2 shared Cleo C. van DiemeniD· 2 shared K. Joeri van der VeldeiD· 2 shared Kristin M. AbbottiD· 2 shared Marielle E van GijniD· 2 shared Morris A. SwertziD· 2 shared Aalt D. J. van DijkiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Bart CharbonORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicineF1000ResearchPeer-reviewedAug 10, 2026

DAVE: how to use explainable AI to interpret missense variants for genome diagnostics based on functional protein modeling

Tim Niemeijer, René Mulder, Helga Westers…·K. Joeri van der Velde

DAVE uses explainable AI to interpret missense variants by integrating biophysically grounded features, improving variant classification and interpretability for genome diagnostics.

DOI 10.12688/f1000research.187527.1

humanwhole-exome sequencing

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Genetic & Genomic MedicineGenome MedicinePeer-reviewedAug 24, 2020

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

Shuang� Li, K. Joeri van der Velde, Dick de Ridder…·Morris A. Swertz

CAPICE is a machine learning method that prioritizes pathogenic variants in exomes, outperforming existing tools for rare and ultra-rare variants.

63 citationstop 5%

whole-exome sequencingmachine learning (classical)

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