AIMC Topic: Metagenome
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CCPred: Global and population-specific colorectal cancer prediction and metagenomic biomarker identification at different molecular levels using machine learning techniques.
Computers in biology and medicine
Sep 17, 2024
Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the comp...
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...
Comprehensive assessment of machine learning methods for diagnosing gastrointestinal diseases through whole metagenome sequencing data.
Gut microbes
Jul 7, 2024
The gut microbiome, linked significantly to host diseases, offers potential for disease diagnosis through machine learning (ML) pipelines. These pipelines, crucial in modeling diseases using high-dimensional microbiome data, involve selecting profile...
Discovery of antimicrobial peptides in the global microbiome with machine learning.
Cell
Jun 5, 2024
Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and...
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...
Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning.
Frontiers in cellular and infection microbiology
May 23, 2024
BACKGROUND: Lower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Lever...
Waste to resource: Mining antimicrobial peptides in sludge from metagenomes using machine learning.
Environment international
Mar 11, 2024
The emergence of antibiotic-resistant bacteria poses a huge threat to the treatment of infections. Antimicrobial peptides are a class of short peptides that widely exist in organisms and are considered as potential substitutes for traditional antibio...
Investigation of machine learning algorithms for taxonomic classification of marine metagenomes.
Microbiology spectrum
Sep 11, 2023
Taxonomic profiling of microbial communities is essential to model microbial interactions and inform habitat conservation. This work develops approaches in constructing training/testing data sets from publicly available marine metagenomes and evaluat...
ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning.
PLoS computational biology
May 1, 2023
The number of published metagenome assemblies is rapidly growing due to advances in sequencing technologies. However, sequencing errors, variable coverage, repetitive genomic regions, and other factors can produce misassemblies, which are challenging...
DL-TODA: A Deep Learning Tool for Omics Data Analysis.
Biomolecules
Mar 24, 2023
Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and acc...
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