AIMC Topic: Metagenome

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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...
Bacteria Protein Processing, Post-Translational Microbiota Peptides Deep Learning Oceans and Seas Metagenome Ribosomes Metagenomics Seawater Bacteriophages
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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...
Adult Male Middle Aged Aged, 80 and over Young Adult Microbiota High-Throughput Nucleotide Sequencing Metagenomics Lung Adolescent Bacteria Humans Machine Learning Female Hospitalization Aged Bronchiectasis Metagenome Respiratory Tract Infections Bronchoalveolar Lavage Fluid
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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...
Anti-Bacterial Agents Machine Learning Bacteria Sewage Metagenomics Antimicrobial Peptides Metagenome
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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...
Metagenome Aquatic Organisms Microbiota Classification Machine Learning Models, Biological Neural Networks, Computer
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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...
Deep Learning Software Genomics Sequence Analysis, DNA Metagenomics Metagenome
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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...
Deep Learning Bacteria Microbiota Humans Metagenome Neural Networks, Computer Algorithms
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Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

mSystems Mar 7, 2023
Comprehensive protein function annotation is essential for understanding microbiome-related disease mechanisms in the host organisms. However, a large portion of human gut microbial proteins lack functional annotation. Here, we have developed a new m...
Humans Deep Learning Metagenome Microbiota Genome, Microbial Molecular Sequence Annotation
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RNN-VirSeeker: A Deep Learning Method for Identification of Short Viral Sequences From Metagenomes.

IEEE/ACM transactions on computational biology and bioinformatics Jun 3, 2022
Viruses are the most abundant biological entities on earth, and play vital roles in many aspects of microbial communities. As major human pathogens, viruses have caused huge mortality and morbidity to human society in history. Metagenomic sequencing ...
Viruses Metagenome Deep Learning Microbiota Metagenomics Humans
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MarkerML - Marker Feature Identification in Metagenomic Datasets Using Interpretable Machine Learning.

Journal of molecular biology Apr 18, 2022
Identification of environment specific marker-features is one of the key objectives of many metagenomic studies. It aims to identify such features in microbiome datasets that may serve as markers of the contrasting or comparable states. Hypothesis te...
Reproducibility of Results Metagenomics Datasets as Topic Humans Machine Learning Metagenome Internet Use
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Multimodal deep learning applied to classify healthy and disease states of human microbiome.

Scientific reports Jan 17, 2022
Metagenomic sequencing methods provide considerable genomic information regarding human microbiomes, enabling us to discover and understand microbial diseases. Compositional differences have been reported between patients and healthy people, which co...
Liver Cirrhosis Microbiota Healthy Volunteers Metagenomics Humans Colorectal Neoplasms Metagenome Inflammatory Bowel Diseases Deep Learning Genome, Microbial Diabetes Mellitus, Type 2
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