AIMC Topic: Metagenomics
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Large-scale machine learning for metagenomics sequence classification.
Bioinformatics (Oxford, England)
Nov 20, 2015
MOTIVATION: Metagenomics characterizes the taxonomic diversity of microbial communities by sequencing DNA directly from an environmental sample. One of the main challenges in metagenomics data analysis is the binning step, where each sequenced read i...
DectICO: an alignment-free supervised metagenomic classification method based on feature extraction and dynamic selection.
BMC bioinformatics
Oct 7, 2015
BACKGROUND: Continual progress in next-generation sequencing allows for generating increasingly large metagenomes which are over time or space. Comparing and classifying the metagenomes with different microbial communities is critical. Alignment-free...
Multi-Layer and Recursive Neural Networks for Metagenomic Classification.
IEEE transactions on nanobioscience
Aug 24, 2015
Recent advances in machine learning, specifically in deep learning with neural networks, has made a profound impact on fields such as natural language processing, image classification, and language modeling; however, feasibility and potential benefit...
Woods: A fast and accurate functional annotator and classifier of genomic and metagenomic sequences.
Genomics
Apr 8, 2015
Functional annotation of the gigantic metagenomic data is one of the major time-consuming and computationally demanding tasks, which is currently a bottleneck for the efficient analysis. The commonly used homology-based methods to functionally annota...
16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
PloS one
Feb 3, 2015
The diversity of microbial species in a metagenomic study is commonly assessed using 16S rRNA gene sequencing. With the rapid developments in genome sequencing technologies, the focus has shifted towards the sequencing of hypervariable regions of 16S...
Unraveling the Role of Gut Microbiota in Colorectal Cancer: A Global Perspectives and Biomarkers as Early Screening Tool for Colorectal Cancer.
Studies in health technology and informatics
Aug 7, 2025
Colorectal cancer (CRC), the second deadliest cancer globally, is closely tied to gut microbiota, opening doors for early detection and treatment. This review of 45 studies (2018-2024) highlights microbial biomarkers like Fusobacterium nucleatum, Bac...
Integrated multi-omics reveals the impact of ruminal keystone bacteria and microbial metabolites on average daily gain in Xuzhou cattle.
Microbiology spectrum
Aug 5, 2025
UNLABELLED: The rumen microbiome plays a crucial role in determining the metabolic and digestive efficiency of livestock. Despite its crucial role, the impact of the rumen microbiome on average daily gain (ADG) in Xuzhou cattle remains underexplored....
VBayesMM: variational Bayesian neural network to prioritize important relationships of high-dimensional microbiome multiomics data.
Briefings in bioinformatics
Jul 2, 2025
The analysis of high-dimensional microbiome multiomics datasets is crucial for understanding the complex interactions between microbial communities and host physiological states across health and disease conditions. Despite their importance, current ...
[Methodological breakthroughs and challenges in research of soil phage microecology].
Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Jun 25, 2025
Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance and genetic diversity. These biological entities serve as critical regulators in Earth's ecosystems...
Genome-resolved metagenomics from short-read sequencing data in the era of artificial intelligence.
Functional & integrative genomics
Jun 10, 2025
Genome-resolved metagenomics is a computational method that enables researchers to reconstruct microbial genomes from a given sample directly. This process involves three major steps, i.e. (i) preprocessing of the reads (ii) metagenome assembly, and ...
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