MARVEL, a Tool for Prediction of Bacteriophage Sequences in Metagenomic Bins

MARVEL, a Tool for Prediction of Bacteriophage Sequences in Metagenomic Bins

Here we present MARVEL, a tool for prediction of double-stranded DNA bacteriophage sequences in metagenomic bins. MARVEL uses a random forest machine learning approach. We trained the program on a dataset with 1,247 phage and 1,029 bacterial genomes, and tested it on a dataset with 335 bacterial and...

Full description

Bibliographic Details
Main Authors: Deyvid Amgarten, Lucas P. P. Braga, Aline M. da Silva, João C. Setubal
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-08-01
Series:Frontiers in Genetics
Subjects:
phage
virus
microbiome
machine learning
random forest
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2018.00304/full

Internet

https://www.frontiersin.org/article/10.3389/fgene.2018.00304/full

Similar Items