Author

Daniel Visentin

Google DeepMind (United Kingdom)

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Genomics· 1

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Assay:ATAC-seq· 1 Assay:ChIP-seq· 1 Research Focus:chromatin & epigenetic regulation· 1 Assay:CRISPR screen· 1 Approach:deep learning· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1

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Agnieszka Grabska‐Barwińska· 1 shared David R. KelleyiD· 1 shared John JumperiD· 1 shared Joseph R. E. LedsamiD· 1 shared Kyle R. TayloriD· 1 shared Pushmeet KohliiD· 1 shared Vikram AgarwaliD· 1 shared Yannis AssaeliD· 1 shared

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2021-2021 · peak 1/yr

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Agnieszka Grabska‐Barwińska

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1 paper

Recent·Most cited

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