Author

Kyle R. Taylor

Google DeepMind (United Kingdom)ORCID 0000-0002-4586-8300Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 3 Organism:human· 3 Research Focus:variant effect prediction· 3 Assay:ChIP-seq· 2 Organism:mouse· 2 Assay:ATAC-seq· 1 Assay:bulk RNA-seq· 1 Research Focus:chromatin & epigenetic regulation· 1

Frequent Co-Authors

Pushmeet KohliiD· 3 shared Adam GayosoiD· 2 shared Anne MottramiD· 2 shared Clare BycroftiD· 2 shared Eirini ArvanitiiD· 2 shared Guido NovatiiD· 2 shared Joshua PaniD· 2 shared Jun ChengiD· 2 shared

Activity by Year

2021-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 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

3 shared papersGenetic & Genomic Medicine

Pushmeet KohliORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

AlphaGenome Atlas: in silico mutagenesis of the entire human genome improves prioritization and interpretation of non-coding variants

Lead authors:, Jun Cheng, Kyle R. Taylor, Lauren Nicolaisen, Joshua Pan, Clare Bycroft, Matteo Perino, Tom Ward, Gareth Hawkes, Laura Covill, Melanie Weilert, Raina W. Thomas, Natasha S. Latysheva, Contributing authors:, Manson Jim, , Žiga Avsec

AlphaGenome Atlas predicts regulatory effects of non-coding variants across the human genome, improving their prioritization and interpretation.

medRxiv · Sep 20, 2026 · PreprintGenetic & Genomic Medicine

AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model

Natasha S. Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft, Lauren Nicolaisen, Eirini Arvaniti, Joshua Pan, Raina W. Thomas, Vincent Dutordoir, Matteo Perino, Soham De, Alexander Karollus, Adam Gayoso, , Pushmeet Kohli

AlphaGenome predicts functional genomic measurements from DNA sequences with high resolution and accuracy across multiple modalities, outperforming existing methods in variant effect prediction.

Nature · Jan 28, 2026Peer-reviewedBioinformatics

Effective gene expression prediction from sequence by integrating long-range interactions

Žiga Avsec, Vikram Agarwal, Daniel Visentin, Joseph R. E. Ledsam, Agnieszka Grabska‐Barwińska, Kyle R. Taylor, Yannis Assael, John Jumper, Pushmeet Kohli, David R. Kelley

Enformer, a sequence-based transformer integrating elements up to 100 kb away, lifts held-out gene expression prediction (correlation 0.81 to 0.85 versus Basenji2) and variant effect prediction.

Nature Methods · Oct 1, 2021Peer-reviewedGenomics✦ In-depth digest