Viral Host

Viral host prediction focuses on identifying the species a virus can infect, crucial for understanding disease emergence and spread. Current research heavily utilizes machine learning, employing various architectures like transformer networks, graph encoder-decoders, and models leveraging position-weight matrices and word embeddings to analyze viral and host protein sequences. These methods aim to improve accuracy and efficiency in predicting host specificity, particularly for rapidly mutating viruses like influenza and coronaviruses, informing public health strategies and vaccine development. The improved prediction of viral hosts has significant implications for pandemic preparedness and the development of targeted antiviral therapies.