SARS CoV 2 Variant

SARS-CoV-2 variant research focuses on understanding the virus's evolution, detecting emerging variants, and predicting their impact. Current research employs diverse computational methods, including deep learning (e.g., convolutional and recurrent neural networks, transformers) for genomic analysis, variant classification, and prediction of future mutations, alongside analyses of epidemiological data and acoustic signals from patients. These efforts aim to improve surveillance, diagnostics, and public health responses to new variants, ultimately contributing to better pandemic preparedness and management. The development of accurate and efficient prediction models is crucial for informing vaccine and therapeutic strategies.