AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Metagenome

Showing 51 to 60 of 73 articles

Clear Filters

Deep learning revealed the distribution and evolution patterns for invertible promoters across bacterial lineages.

Nucleic acids research
Invertible promoters (invertons) are crucial regulatory elements in bacteria, facilitating gene expression changes under stress. Despite their importance, their prevalence and the range of regulated gene functions are largely unknown. We introduced D...

VirDetect-AI: a residual and convolutional neural network-based metagenomic tool for eukaryotic viral protein identification.

Briefings in bioinformatics
This study addresses the challenging task of identifying viruses within metagenomic data, which encompasses a broad array of biological samples, including animal reservoirs, environmental sources, and the human body. Traditional methods for virus ide...

MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework.

Briefings in bioinformatics
The gut microbiota plays a vital role in human health, and significant effort has been made to predict human phenotypes, especially diseases, with the microbiota as a promising indicator or predictor with machine learning (ML) methods. However, the a...

DeepCheck: multitask learning aids in assessing microbial genome quality.

Briefings in bioinformatics
Metagenomic analyses facilitate the exploration of the microbial world, advancing our understanding of microbial roles in ecological and biological processes. A pivotal aspect of metagenomic analysis involves assessing the quality of metagenome-assem...

Deep learning methods in metagenomics: a review.

Microbial genomics
The ever-decreasing cost of sequencing and the growing potential applications of metagenomics have led to an unprecedented surge in data generation. One of the most prevalent applications of metagenomics is the study of microbial environments, such a...

CoCoPyE: feature engineering for learning and prediction of genome quality indices.

GigaScience
BACKGROUND: The exploration of the microbial world has been greatly advanced by the reconstruction of genomes from metagenomic sequence data. However, the rapidly increasing number of metagenome-assembled genomes has also resulted in a wide variation...

PLM-ARG: antibiotic resistance gene identification using a pretrained protein language model.

Bioinformatics (Oxford, England)
MOTIVATION: Antibiotic resistance presents a formidable global challenge to public health and the environment. While considerable endeavors have been dedicated to identify antibiotic resistance genes (ARGs) for assessing the threat of antibiotic resi...

DeepToA: an ensemble deep-learning approach to predicting the theater of activity of a microbiome.

Bioinformatics (Oxford, England)
MOTIVATION: Metagenomics is the study of microbiomes using DNA sequencing. A microbiome consists of an assemblage of microbes that is associated with a 'theater of activity' (ToA). An important question is, to what degree does the taxonomic and funct...

Virtifier: a deep learning-based identifier for viral sequences from metagenomes.

Bioinformatics (Oxford, England)
MOTIVATION: Viruses, the most abundant biological entities on earth, are important components of microbial communities, and as major human pathogens, they are responsible for human mortality and morbidity. The identification of viral sequences from m...

Tiara: deep learning-based classification system for eukaryotic sequences.

Bioinformatics (Oxford, England)
MOTIVATION: With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding ...