ArticleOphthalmology science2026
Deep Learning and Experimental Validation of BRCA1-Associated Protein-1 Missense Variant Pathogenicity in Uveal Melanoma.
Article in Ophthalmology science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
Objective: To benchmark the pathogenicity predictions of AlphaMissense, a deep learning model, against high-throughput functional scores from saturation genome editing (SGE) for all experimentally tested Design: Cross-sectional analytical study comparing computational predictions with experimentally derived functional classifications and clinical annotations. Subjects Participants and/or Controls: ClusteredAll 4619 Methods: Saturation genome editing log Main Outcome Measures: (1) Concordance between in silico predictors and SGE labels (area under ROC and PR curves); (2) agreement with ClinVar classifications; (3) structural clustering of high-risk residues. Results: Of the 4619 Conclusions: AlphaMissense aligns closely with the gold standard functional data for Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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