AIMC Topic: Metagenome

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PlasGUN: gene prediction in plasmid metagenomic short reads using deep learning.

Bioinformatics (Oxford, England)
SUMMARY: We present the first tool of gene prediction, PlasGUN, for plasmid metagenomic short-read data. The tool, developed based on deep learning algorithm of multiple input Convolutional Neural Network, demonstrates much better performance when te...

Protein contact prediction using metagenome sequence data and residual neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Almost all protein residue contact prediction methods rely on the availability of deep multiple sequence alignments (MSAs). However, many proteins from the poorly populated families do not have sufficient number of homologs in the convent...

VHost-Classifier: virus-host classification using natural language processing.

Bioinformatics (Oxford, England)
MOTIVATION: When analyzing viral metagenomic sequences, it is often desired to filter the results of a BLAST analysis by the host species of the virus. VHost-Classifier automates this procedure using a natural language processing algorithm written in...

PPR-Meta: a tool for identifying phages and plasmids from metagenomic fragments using deep learning.

GigaScience
BACKGROUND: Phages and plasmids are the major components of mobile genetic elements, and fragments from such elements generally co-exist with chromosome-derived fragments in sequenced metagenomic data. However, there is a lack of efficient methods th...