SCV Filter: A Hybrid Deep Learning Model for SARS-CoV-2 Variants
Classification
Han Wang,
Jingyang Gao
Abstract:Background:
The high mutability of severe acute respiratory syndrome coronavirus
2(SARS-CoV-2) makes it easy for mutations to occur during transmission. As the epidemic continues to
develop, several mutated strains have been produced. Researchers worldwide are working on the effective
identification of SARS-CoV-2.
Objective:
In this paper, we propose a new deep learning method that can effectively identify SARSCoV-
2 Variant sequences, called SCVfilter, which is a deep hybrid model with embedding, attention
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