APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial misse...
APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants
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Author / Creator
Bianco, Salvatore Daniele , Parca, Luca , Petrizzelli, Francesco , Biagini, Tommaso , Giovannetti, Agnese , Liorni, Niccolò , Napoli, Alessandro , Carella, Massimo , Procaccio, Vincent , Lott, Marie T. , Zhang, Shiping , Vescovi, Angelo Luigi , Wallace, Douglas C. , Caputo, Viviana and Mazza, Tommaso
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
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 APOGEE 2, a mitochondrially-centered ensemble method designed...
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Full title
APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants
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TN_cdi_doaj_primary_oai_doaj_org_article_64f1c2068b1f4c58ae29cd7b9a674f0e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_64f1c2068b1f4c58ae29cd7b9a674f0e
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-023-40797-7
