Zero-shot-capable identification of phage-host relationships with whole-genome sequence representation by contrastive learning.

ABSTRACT: Accurately identifying phage-host relationships from their genome sequences is still challenging, especially for those phages and hosts with less homologous sequences. In this work, focusing on identifying the phage-host relationships at the species and genus level, we propose a contrastive learning based approach to learn whole-genome sequence embeddings that can take account of phage-host interactions (PHIs). Contrastive learning is used to make phages infecting the same hosts close to each other in the new representation space. Specifically, we rephrase whole-genome sequences with frequency chaos game representation (FCGR) and learn latent embeddings that 'encapsulate' phages and host relationships through contrastive learning. The contrastive learning method works well on the imbalance

SUBMITTER: Zhang YZ 

PROVIDER: S-EPMC10516345 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature