[HTML][HTML] iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria
The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied
through metagenomics. While metagenomes enable high-throughput exploration of the viral …
through metagenomics. While metagenomes enable high-throughput exploration of the viral …
[PDF][PDF] RaFAH: Host prediction for viruses of Bacteria and Archaea based on protein content
Culture-independent approaches have recently shed light on the genomic diversity of
viruses of prokaryotes. One fundamental question when trying to understand their ecological …
viruses of prokaryotes. One fundamental question when trying to understand their ecological …
[HTML][HTML] Prokaryotic virus host predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics
Background Viruses are ubiquitous biological entities, estimated to be the largest reservoirs
of unexplored genetic diversity on Earth. Full functional characterization and annotation of …
of unexplored genetic diversity on Earth. Full functional characterization and annotation of …
Computational approaches to predict bacteriophage–host relationships
Metagenomics has changed the face of virus discovery by enabling the accurate
identification of viral genome sequences without requiring isolation of the viruses. As a …
identification of viral genome sequences without requiring isolation of the viruses. As a …
Alignment-free oligonucleotide frequency dissimilarity measure improves prediction of hosts from metagenomically-derived viral sequences
Viruses and their host genomes often share similar oligonucleotide frequency (ONF)
patterns, which can be used to predict the host of a given virus by finding the host with the …
patterns, which can be used to predict the host of a given virus by finding the host with the …
[HTML][HTML] VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data
Background Identifying viral sequences in mixed metagenomes containing both viral and
host contigs is a critical first step in analyzing the viral component of samples. Current tools …
host contigs is a critical first step in analyzing the viral component of samples. Current tools …
Virtifier: a deep learning-based identifier for viral sequences from metagenomes
Y Miao, F Liu, T Hou, Y Liu - Bioinformatics, 2022 - academic.oup.com
Motivation Viruses, the most abundant biological entities on earth, are important
components of microbial communities, and as major human pathogens, they are …
components of microbial communities, and as major human pathogens, they are …
IMG/VR v. 2.0: an integrated data management and analysis system for cultivated and environmental viral genomes
D Paez-Espino, S Roux, IMA Chen… - Nucleic acids …, 2019 - academic.oup.com
Abstract The Integrated Microbial Genome/Virus (IMG/VR) system v. 2.0 (https://img. jgi. doe.
gov/vr/) is the largest publicly available data management and analysis platform dedicated …
gov/vr/) is the largest publicly available data management and analysis platform dedicated …
A network-based integrated framework for predicting virus–prokaryote interactions
Metagenomic sequencing has greatly enhanced the discovery of viral genomic sequences;
however, it remains challenging to identify the host (s) of these new viruses. We developed …
however, it remains challenging to identify the host (s) of these new viruses. We developed …
VIDHOP, viral host prediction with deep learning
Motivation Zoonosis, the natural transmission of infections from animals to humans, is a far-
reaching global problem. The recent outbreaks of Zikavirus, Ebolavirus and Coronavirus are …
reaching global problem. The recent outbreaks of Zikavirus, Ebolavirus and Coronavirus are …