AIMC Topic: Microbiota

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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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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 Machine Learning Metagenomics Data Analysis Metagenome
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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 ...
Machine Learning Cities Bacteria Metagenomics Microbiota High-Throughput Nucleotide Sequencing
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Microbiome composition and implications for ballast water classification using machine learning.

The Science of the total environment Jul 4, 2019
Ballast water is a vector for global translocation of microorganisms, and should be monitored to protect human and environmental health. This study utilizes high throughput sequencing (HTS) and machine learning to examine the bacterial and fungal mic...
Environmental Monitoring Machine Learning Water Microbiology Microbiota Ships
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Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition.

PloS one Jul 1, 2019
Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems they inhabit. However, deciphering the functional relationship between specific microbes and ecosystem properties is an ongoing challenge owing to the c...
Carbon Microbiota RNA, Ribosomal, 16S Machine Learning Sequence Analysis, DNA Bacteria
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A neural network model predicts community-level signaling states in a diverse microbial community.

PLoS computational biology Jun 24, 2019
Signal crosstalk within biological communication networks is common, and such crosstalk can have unexpected consequences for decision making in heterogeneous communities of cells. Here we examined crosstalk within a bacterial community composed of fi...
Microbiota Quorum Sensing Bacillus subtilis Models, Biological Computational Biology Signal Transduction Neural Networks, Computer
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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...
Support Vector Machine Databases, Genetic Area Under Curve ROC Curve Models, Theoretical Microbiota Metagenomics Humans Neural Networks, Computer Algorithms Phenotype Machine Learning
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Learning Single-Cell Distances from Cytometry Data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology May 17, 2019
Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric, a function that quantif...
Machine Learning Algorithms Humans Pattern Recognition, Automated Cluster Analysis Blood Cells Single-Cell Analysis Flow Cytometry Bacteria Microbiota
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Modelling the influence of environmental parameters over marine planktonic microbial communities using artificial neural networks.

The Science of the total environment Apr 26, 2019
Guanabara Bay is a tropical estuarine ecosystem that receives massive anthropogenic impacts from the metropolitan region of Rio de Janeiro. This ecosystem suffers from an ongoing eutrophication process that has been shown to promote the emergence of ...
Plankton Bays Models, Biological Microbiota Brazil Neural Networks, Computer Environmental Monitoring
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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...
Metagenomics Metagenome Phylogeny Pharynx High-Throughput Nucleotide Sequencing Support Vector Machine Decision Trees Databases, Genetic Microbiota Humans Algorithms
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