APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

Abstract Mitochondrial dysfunction has pleiotropic effects and is frequently caused by mitochondrial DNA mutations. However, factors such as significant variability in clinical manifestations make interpreting the pathogenicity of variants in the mitochondrial genome challenging. Here, we present AP...

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Bibliographic Details
Main Authors: Salvatore Daniele Bianco, Luca Parca, Francesco Petrizzelli, Tommaso Biagini, Agnese Giovannetti, Niccolò Liorni, Alessandro Napoli, Massimo Carella, Vincent Procaccio, Marie T. Lott, Shiping Zhang, Angelo Luigi Vescovi, Douglas C. Wallace, Viviana Caputo, Tommaso Mazza
Format: Article
Language:English
Published: Nature Portfolio 2023-08-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-023-40797-7

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https://doi.org/10.1038/s41467-023-40797-7

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