AIMC Topic: Bacteriophages
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Optimizing phage therapy with artificial intelligence: a perspective.
Frontiers in cellular and infection microbiology
May 27, 2025
Phage therapy is emerging as a promising strategy against the growing threat of antimicrobial resistance, yet phage and bacteria are incredibly diverse and idiosyncratic in their interactions with one another. Clinical applications of phage therapy o...
PhageDPO: A machine-learning based computational framework for identifying phage depolymerases.
Computers in biology and medicine
Feb 13, 2025
Bacteriophages (phages) are the most predominant and genetically diverse biological entities on Earth. Phages are viruses that infect bacteria and encode numerous proteins with potential biotechnological application. However, most phage-encoded prote...
Bacteriophage-Activated DNAzyme Hydrogels Combined with Machine Learning Enable Point-of-Use Colorimetric Detection of Escherichia coli.
Advanced materials (Deerfield Beach, Fla.)
Nov 26, 2024
Developing cost-effective, consumer-accessible platforms for point-of-use environmental and clinical pathogen testing is a priority, to reduce reliance on laborious, time-consuming culturing approaches. Unfortunately, a system offering ultrasensitive...
Improving viral annotation with artificial intelligence.
mBio
Sep 4, 2024
Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environme...
Discovery of Antimicrobial Lysins from the "Dark Matter" of Uncharacterized Phages Using Artificial Intelligence.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jun 20, 2024
The rapid rise of antibiotic resistance and slow discovery of new antibiotics have threatened global health. While novel phage lysins have emerged as potential antibacterial agents, experimental screening methods for novel lysins pose significant cha...
Exploring the roles of ribosomal peptides in prokaryote-phage interactions through deep learning-enabled metagenome mining.
Microbiome
May 24, 2024
BACKGROUND: Microbial secondary metabolites play a crucial role in the intricate interactions within the natural environment. Among these metabolites, ribosomally synthesized and post-translationally modified peptides (RiPPs) are becoming a promising...
Prediction of Klebsiella phage-host specificity at the strain level.
Nature communications
May 22, 2024
Phages are increasingly considered promising alternatives to target drug-resistant bacterial pathogens. However, their often-narrow host range can make it challenging to find matching phages against bacteria of interest. Current computational tools d...
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....
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