AIMC Topic: Metagenomics

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Application of machine learning techniques for creating urban microbial fingerprints.

Biology direct Aug 16, 2019
BACKGROUND: Research has found that human associated microbial communities play a role in homeostasis and the disruption of these communities may be important in an array of medical conditions. However outside of the human body many of these communit...
Metagenomics Metagenome DNA Fingerprinting Cities Microbiota Machine Learning
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Hierarchical Hidden Markov models enable accurate and diverse detection of antimicrobial resistance sequences.

Communications biology Aug 6, 2019
The characterization of antimicrobial resistance genes from high-throughput sequencing data has become foundational in public health research and regulation. This requires mapping sequence reads to databases of known antimicrobial resistance genes to...
Machine Learning Sequence Analysis, DNA Metagenomics High-Throughput Nucleotide Sequencing Drug Resistance, Microbial Markov Chains Reproducibility of Results Data Mining Databases, Genetic
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Massive metagenomic data analysis using abundance-based machine learning.

Biology direct Aug 1, 2019
BACKGROUND: Metagenomics is the application of modern genomic techniques to investigate the members of a microbial community directly in their natural environments and is widely used in many studies to survey the communities of microbial organisms th...
Microbiota Metagenomics Metagenome Machine Learning Data Analysis
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Identification of city specific important bacterial signature for the MetaSUB CAMDA challenge microbiome data.

Biology direct Jul 24, 2019
BACKGROUND: Metagenomic data of whole genome sequences (WGS) from samples across several cities around the globe may unravel city specific signatures of microbes. Illumina MiSeq sequencing data was provided from 12 cities in 7 different countries as ...
Bacteria Machine Learning Microbiota Cities High-Throughput Nucleotide Sequencing Metagenomics
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MetaNN: accurate classification of host phenotypes from metagenomic data using neural networks.

BMC bioinformatics Jun 20, 2019
BACKGROUND: Microbiome profiles in the human body and environment niches have become publicly available due to recent advances in high-throughput sequencing technologies. Indeed, recent studies have already identified different microbiome profiles in...
Neural Networks, Computer Machine Learning Algorithms Humans Models, Theoretical Support Vector Machine Databases, Genetic Phenotype ROC Curve Metagenomics Area Under Curve Microbiota
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Sparse support vector machines with L approximation for ultra-high dimensional omics data.

Artificial intelligence in medicine Apr 30, 2019
Omics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L norm for the primal variables, only lead to sparse solutions for the dual variables. L based SVMs, directly mini...
Humans Gene Expression Support Vector Machine Artificial Intelligence Metagenomics
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Phy-PMRFI: Phylogeny-Aware Prediction of Metagenomic Functions Using Random Forest Feature Importance.

IEEE transactions on nanobioscience Apr 24, 2019
High-throughput sequencing techniques have accelerated functional metagenomics studies through the generation of large volumes of omics data. The integration of these data using computational approaches is potentially useful for predicting metagenomi...
Metagenome Decision Trees Microbiota High-Throughput Nucleotide Sequencing Metagenomics Pharynx Phylogeny Support Vector Machine Databases, Genetic Humans Algorithms
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MetaPheno: A critical evaluation of deep learning and machine learning in metagenome-based disease prediction.

Methods (San Diego, Calif.) Mar 16, 2019
The human microbiome plays a number of critical roles, impacting almost every aspect of human health and well-being. Conditions in the microbiome have been linked to a number of significant diseases. Additionally, revolutions in sequencing technology...
Humans Algorithms Deep Learning Machine Learning Microbiota Metagenomics Diabetes Mellitus, Type 2 Metagenome Obesity
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OMeta: an ontology-based, data-driven metadata tracking system.

BMC bioinformatics Jan 7, 2019
BACKGROUND: The development of high-throughput sequencing and analysis has accelerated multi-omics studies of thousands of microbial species, metagenomes, and infectious disease pathogens. Omics studies are enabling genotype-phenotype association stu...
Biological Ontologies Whole Genome Sequencing Metagenomics Metadata Software Phylogeny Databases, Factual User-Computer Interface
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Embracing Environmental Genomics and Machine Learning for Routine Biomonitoring.

Trends in microbiology Dec 13, 2018
Genomics is fast becoming a routine tool in medical diagnostics and cutting-edge biotechnologies. Yet, its use for environmental biomonitoring is still considered a futuristic ideal. Until now, environmental genomics was mainly used as a replacement ...
Genetic Variation Metagenomics Environmental Microbiology DNA Barcoding, Taxonomic Machine Learning Ecosystem Environmental Monitoring Microbiota Bacteria
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