Author

Yee Whye Teh

University of OxfordORCID 0000-0001-5365-6933Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Assay:DNA methylation· 1 Approach:graph neural network· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

A. Marieke OudelaariD· 1 shared Carlos OuteiraliD· 1 shared Charlotte Mary DeaneiD· 1 shared Damien J. DownesiD· 1 shared Gerton A. LunteriD· 1 shared Jelena M. TeleniusiD· 1 shared Jim R. HughesiD· 1 shared Matteo CagiadaiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperGenomics

A. Marieke OudelaarORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintMay 29, 2026

Just Add Structure: Protein Language Models Combined with Structural Equivariance Excel at Protein Tasks

Qurat-ul-ain, Carlos Outeiral, Matteo Cagiada…·Charlotte Mary Deane

This paper introduces ProtEGNN, a model combining protein language models with geometric equivariance to improve protein property and function prediction with fewer parameters than fine-tuned PLMs.

DOI 10.64898/2026.05.28.728196

protein sequencegraph neural network

𝕏 PostBluesky

GenomicsNature MethodsPeer-reviewedOct 12, 2020

DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning.

Ron Schweßinger, Matthew E. Gosden, Damien J. Downes…·Jim R. Hughes

DeepC predicts chromatin interactions from DNA sequence using deep learning and transfer learning, generalizing across cell types and resolutions.

222 citationstop 1%

DNA methylationwhole-genome sequencing

𝕏 PostBluesky