A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction.

ABSTRACT: Multi-drug resistance (MDR) has become one of the greatest threats to human health worldwide, and novel treatment methods of infections caused by MDR bacteria are urgently needed. Phage therapy is a promising alternative to solve this problem, to which the key is correctly matching target pathogenic bacteria with the corresponding therapeutic phage. Deep learning is powerful for mining complex patterns to generate accurate predictions. In this study, we develop PredPHI (Predicting Phage-Host Interactions), a deep learning-based tool capable of predicting the host of phages from sequence data. We collect >3000 phage-host pairs along with their protein sequences from PhagesDB and GenBank databases and extract a set of features. Then we select high-quality negative samples based on the K-Mean

SUBMITTER: Li M 

PROVIDER: S-EPMC8703204 | biostudies-literature | 2021 Sep-Oct

REPOSITORIES: biostudies-literature