Predicting the hosts of prokaryotic viruses using GCN-based semi-supervised learning.

ABSTRACT:

Background

Prokaryotic viruses, which infect bacteria and archaea, are the most abundant and diverse biological entities in the biosphere. To understand their regulatory roles in various ecosystems and to harness the potential of bacteriophages for use in therapy, more knowledge of viral-host relationships is required. High-throughput sequencing and its application to the microbiome have offered new opportunities for computational approaches for predicting which hosts particular viruses can infect. However, there are two main challenges for computational host prediction. First, the empirically known virus-host relationships are very limited. Second, although sequence similarity between viruses and their prokaryote hosts have been used as a major feature for host prediction, the ali

SUBMITTER: Shang J 

PROVIDER: S-EPMC8611875 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature