| Literature DB >> 31114893 |
Wenchen Song1,2,3, Hai-Xi Sun1,2, Carolyn Zhang4, Li Cheng1,2,5, Ye Peng1,2,5, Ziqing Deng1,2, Dan Wang1,2, Yun Wang1,2, Ming Hu3, Wenen Liu6, Huanming Yang1,2, Yue Shen1,2, Junhua Li1,2,5, Lingchong You4,7,8, Minfeng Xiao1,2.
Abstract
Identifying active prophages is critical for studying coevolution of phage and bacteria, investigating phage physiology and biochemistry, and engineering designer phages for diverse applications. We present Prophage Hunter, a tool aimed at hunting for active prophages from whole genome assembly of bacteria. Combining sequence similarity-based matching and genetic features-based machine learning classification, we developed a novel scoring system that exhibits higher accuracy than current tools in predicting active prophages on the validation datasets. The option of skipping similarity matching is also available so that there's higher chance for novel phages to be discovered. Prophage Hunter provides a one-stop web service to extract prophage genomes from bacterial genomes, evaluate the activity of the prophages, identify phylogenetically related phages, and annotate the function of phage proteins. Prophage Hunter is freely available at https://pro-hunter.bgi.com/.Entities:
Year: 2019 PMID: 31114893 PMCID: PMC6602508 DOI: 10.1093/nar/gkz380
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971