Author

Henry Kenlay

University of CambridgeORCID 0000-0002-6741-2494Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Approach:deep learning· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1

Frequent Co-Authors

Aleksandr KovaltsukiD· 1 shared Alex Hawkins‐HookeriD· 1 shared Charlotte Mary DeaneiD· 1 shared Claire MarksiD· 1 shared Constantin SchneideriD· 1 shared Daniel Allen NissleyiD· 1 shared Daniel CuttingiD· 1 shared Daniel L. HurdissiD· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Aleksandr KovaltsukORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Computational design of developable therapeutic antibodies: efficient traversal of binder landscapes and rescue of escape mutations

Frédéric A. Dreyer, Constantin Schneider, Aleksandr Kovaltsuk, Daniel Cutting, Matthew J. Byrne, Daniel Allen Nissley, Newton Wahome, Henry Kenlay, Claire Marks, David Errington, Richard J. Gildea, David Damerell, Pedro A. G. Tizei, Wilawan Bunjobpol, John F. Darby, , Charlotte Mary Deane

This paper presents a computational pipeline for designing therapeutic antibodies using AI and physics-based methods, showing improved binding and developability across SARS-CoV-2 variants.

bioRxiv · Oct 3, 2024 · PreprintBioinformatics

Projection layers improve deep learning models of regulatory DNA function

Alex Hawkins‐Hooker, Henry Kenlay, John E. Reid

The paper introduces a projection layer to improve deep learning models for regulatory DNA function prediction, showing performance gains on the DeepSEA dataset.

F1000Research · Feb 5, 2019Peer-reviewedBioinformatics