Author

Nick Geukens

KU LeuvenPrimary ORCID profile (0000-0001-5706-1072 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Nick GeukensiD1 paper · KU Leuven

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Organism:mouse· 1 Research Focus:protein design· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexander N. VolkoviD· 1 shared Carlo CarolisiD· 1 shared Damiano CianferoniiD· 1 shared David VizarragaiD· 1 shared Frédéric RousseauiD· 1 shared Gabriel CiaiD· 1 shared Gabriele OrlandoiD· 1 shared Iva MarkovićiD· 1 shared

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2024-2024 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alexander N. VolkovORCID

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1 paper

Recent·Most cited

In silico design of stable single-domain antibodies with high affinity

Zhongyao Zhang, Rob van der Kant, Iva Marković, David Vizarraga, Teresa Garcia, Katerina Maragkou, Javier Delgado, Damiano Cianferoni, Gabriele Orlando, Gabriel Cia, Nick Geukens, Carlo Carolis, Alexander N. Volkov, Savvas N. Savvides, Maarten Dewilde, , Frédéric Rousseau

This paper introduces EvolveX, a computational pipeline for designing stable single-domain antibodies with high affinity, demonstrating improved binding affinity to human targets.

bioRxiv · Apr 22, 2024 · PreprintBioinformatics