Precise uncertain significance prediction using latent space matrix factorization models: genomics variant and heterogeneous clinical data-driven approaches.

Abstract excerpt

Several studies to date have proposed different types of interpreters for measuring the degree of pathogenicity of variants. However, in predicting the disease type and disease-gene associations, scholars face two essential challenges, namely the vast number of existing variants and the existence of variants which are recognized as variant of uncertain significance (VUS). To tackle these challenges, we propose...

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