METAMVGL: a multi-view graph-based metagenomic contig binning algorithm by integrating assembly and paired-end graphs.

Published in: BMC bioinformatics (2021)

Our findings demonstrate METAMVGL outstandingly improves the short contig binning and outperforms the other existing contig binning tools on the metagenomic sequencing data from simulation, mock communities and infant fecal samples.

Keyphrases

antibiotic resistance genes
electronic health record
neural network
deep learning
single cell
convolutional neural network
wastewater treatment
microbial community
anaerobic digestion