Bacteriophage host prediction using a genome language model
This study demonstrates that unsupervised embeddings from the pretrained Evo2 genome language model capture meaningful host-range signals for bacteriophages, achieving competitive retrieval performance that is further enhanced when combined with traditional alignment and k-mer-based methods in a hybrid pipeline.