Transformers significantly improve splice site prediction

Transformers significantly improve splice site prediction

Abstract Mutations that affect RNA splicing significantly impact human diversity and disease. Here we present a method using transformers, a type of machine learning model, to detect splicing from raw 45,000-nucleotide sequences. We generate embeddings with residual neural networks and apply hard at...

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Main Authors: Benedikt A. Jónsson, Gísli H. Halldórsson, Steinþór Árdal, Sölvi Rögnvaldsson, Eyþór Einarsson, Patrick Sulem, Daníel F. Guðbjartsson, Páll Melsted, Kári Stefánsson, Magnús Ö. Úlfarsson
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-024-07298-9
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https://doi.org/10.1038/s42003-024-07298-9

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