A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction

A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction

Introduction: Variants in 5′ and 3′ untranslated regions (UTR) contribute to rare disease. While predictive algorithms to assist in classifying pathogenicity can potentially be highly valuable, the utility of these tools is often unclear, as it depends on carefully selected training and validation c...

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Bibliographic Details
Main Authors: Emma Bohn, Tammy T. Y. Lau, Omar Wagih, Tehmina Masud, Daniele Merico
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Molecular Biosciences
Subjects:
deep learning
non-coding variation
rare disease
untranslated region (UTR)
variant classification
Online Access:https://www.frontiersin.org/articles/10.3389/fmolb.2023.1257550/full

Internet

https://www.frontiersin.org/articles/10.3389/fmolb.2023.1257550/full

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