Article

Self-attention based deep learning model for predicting the coronavirus sequences from high-throughput sequencing data

2024-08-07

Abstract excerpt

Transformer models have achieved excellent results in various tasks, primarily due to the self-attention mechanism. We explore using self-attention for detecting coronavirus sequences in high-throughput sequencing data, offering a novel approach for accurately identifying emerging and highly variable coronavirus strains. Coronavirus and human genome data were obtained from the Genomic Data Commons (GDC) and the Na...

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Literature Corpus work: 0dc25a7c-0ee2-5aec-b117-82b2143851ff
DOI: 10.1101/2024.08.07.24311618

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