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DeepSVP is a machine learning model that takes as input a set of SVs in Variant Call Format (VCF) format together with a set of phenotypes encoded using the ...
We developed DeepSVP, a computational method to prioritize structural variants involved in genetic diseases by combining genomic and gene functions information.
PDF | Motivation Structural genomic variants account for much of human variability and are involved in several diseases. Structural variants are complex.
Apr 9, 2021 · DeepSVP: Integration of genotype and phenotype for structural variant prioritization using deep learning · Find this author on Google Scholar ...
We developed DeepSVP, a computational method to prioritize structural variants involved in genetic diseases by combining genomic and gene functions information.
Another tool, DeepSVP, combined an ontology-based deep learning module to match genes and phenotypes with a deep neural network module to predict whether a ...
Dec 24, 2021 · Dive into the research topics of 'DeepSVP: Integration of genotype and phenotype for structural variant prioritization using deep learning'.
DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning. https://doi.org/10.1093/bioinformatics/btab859 ...
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Nov 28, 2023 · Here, we introduce PhenoSV, a phenotype-aware machine-learning model that interprets all major types of SVs and genes affected.
Sep 9, 2024 · DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning. Bioinformatics. 2022; 38:1677-1684.