AIMC Topic: Bacteriophages
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Identifying ARG-carrying bacteriophages in a lake replenished by reclaimed water using deep learning techniques.
Water research
Nov 11, 2023
As important mobile genetic elements, phages support the spread of antibiotic resistance genes (ARGs). Previous analyses of metaviromes or metagenome-assembled genomes (MAGs) failed to assess the extent of ARGs transferred by phages, particularly in ...
DPProm: A Two-Layer Predictor for Identifying Promoters and Their Types on Phage Genome Using Deep Learning.
IEEE journal of biomedical and health informatics
Oct 4, 2022
With the number of phage genomes increasing, it is urgent to develop new bioinformatics methods for phage genome annotation. Promoter, a DNA region, is important for gene transcriptional regulation. In the era of post-genomics, the availability of da...
Anti-CRISPR prediction using deep learning reveals an inhibitor of Cas13b nucleases.
Molecular cell
May 31, 2022
As part of the ongoing bacterial-phage arms race, CRISPR-Cas systems in bacteria clear invading phages whereas anti-CRISPR proteins (Acrs) in phages inhibit CRISPR defenses. Known Acrs have proven extremely diverse, complicating their identification....
PhageLeads: Rapid Assessment of Phage Therapeutic Suitability Using an Ensemble Machine Learning Approach.
Viruses
Feb 8, 2022
The characterization of therapeutic phage genomes plays a crucial role in the success rate of phage therapies. There are three checkpoints that need to be examined for the selection of phage candidates, namely, the presence of temperate markers, anti...
A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Multi-drug resistance (MDR) has become one of the greatest threats to human health worldwide, and novel treatment methods of infections caused by MDR bacteria are urgently needed. Phage therapy is a promising alternative to solve this problem, to whi...
Application of machine learning in bacteriophage research.
BMC microbiology
Jun 26, 2021
Phages are one of the key components in the structure, dynamics, and interactions of microbial communities in different bins. It has a clear impact on human health and the food industry. Bacteriophage characterization using in vitro approaches are ti...
Machine-learning approach expands the repertoire of anti-CRISPR protein families.
Nature communications
Jul 29, 2020
The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechani...
Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.
Journal of computer-aided molecular design
Jun 16, 2020
Phage virion protein (PVP) perforate the host cell membrane and eventually culminates in cell rupture thereby releasing replicated phages. The accurate identification of PVP is thus a crucial step towards improving our understanding of the biological...
Review and comparative analysis of machine learning-based phage virion protein identification methods.
Biochimica et biophysica acta. Proteins and proteomics
Mar 2, 2020
Phage virion protein (PVP) identification plays key role in elucidating relationships between phages and hosts. Moreover, PVP identification can facilitate the design of related biochemical entities. Recently, several machine learning approaches have...
Computational prediction of inter-species relationships through omics data analysis and machine learning.
BMC bioinformatics
Nov 20, 2018
BACKGROUND: Antibiotic resistance and its rapid dissemination around the world threaten the efficacy of currently-used medical treatments and call for novel, innovative approaches to manage multi-drug resistant infections. Phage therapy, i.e., the us...
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