{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["5(3)"],"submitter":["Taylor Gonzalez DJ"],"pubmed_abstract":["<h4>Objective</h4>Uveal melanoma (UM) poses significant diagnostic and prognostic challenges due to its variable genetic landscape. We explore the use of a novel deep learning tool to assess the functional impact of genetic mutations in UM.<h4>Design</h4>A cross-sectional bioinformatics exploratory data analysis of genetic mutations from UM cases.<h4>Subjects</h4>Genetic data from patients diagnosed with UM were analyzed, explicitly focusing on missense mutations sourced from the Catalogue of Somatic Mutations in Cancer (COSMIC) database.<h4>Methods</h4>We identified missense mutations frequently observed in UM using the COSMIC database, assessed their potential pathogenicity using AlphaMissense, and visualized mutations using AlphaFold. Clinical significance was cross-validated with entri"],"journal":["Ophthalmology science"],"pagination":["100673"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11925568"],"repository":["biostudies-literature"],"pubmed_title":["AlphaMissense Predictions and ClinVar Annotations: A Deep Learning Approach to Uveal Melanoma."],"pmcid":["PMC11925568"],"pubmed_authors":["Antonietti M","Shields CL","Taylor Gonzalez DJ","Uversky VN","Karp CL","Wilson MW","Djulbegovic MB","Kim CK","Sharma M"],"additional_accession":[]},"is_claimable":false,"name":"AlphaMissense Predictions and ClinVar Annotations: A Deep Learning Approach to Uveal Melanoma.","description":"<h4>Objective</h4>Uveal melanoma (UM) poses significant diagnostic and prognostic challenges due to its variable genetic landscape. We explore the use of a novel deep learning tool to assess the functional impact of genetic mutations in UM.<h4>Design</h4>A cross-sectional bioinformatics exploratory data analysis of genetic mutations from UM cases.<h4>Subjects</h4>Genetic data from patients diagnosed with UM were analyzed, explicitly focusing on missense mutations sourced from the Catalogue of Somatic Mutations in Cancer (COSMIC) database.<h4>Methods</h4>We identified missense mutations frequently observed in UM using the COSMIC database, assessed their potential pathogenicity using AlphaMissense, and visualized mutations using AlphaFold. Clinical significance was cross-validated with entri","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 May-Jun","modification":"2025-04-04T03:03:46.44Z","creation":"2025-04-04T03:03:46.44Z"},"accession":"S-EPMC11925568","cross_references":{"pubmed":["40114711"],"doi":["10.1016/j.xops.2024.100673"]}}