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 rRNA gene instead of full length gene sequencing. Therefore, 16S Classifier is developed using a machine learning method, Random Forest, for faster and accurate taxonomic classification of short hypervariable regions of 16S rRNA sequence. It displayed precision values of up to 0.91 on training datasets and the precision values of up to 0.98 on the test dataset. On real metagenomic datasets, it showed up to 99.7% accuracy at the phylum level and up to 99.0% accuracy at the genus level. 16S Class...
<p>Background: Current sequencing technology enables taxonomic profiling of microbial ecosystems at ...
Background: A 16S rRNA sequence represents a marker gene commonly used for taxonomic annotation of b...
Background: An open challenge in translational bioinformatics is the analysis of sequenced metagenom...
<div><p>The diversity of microbial species in a metagenomic study is commonly assessed using 16S rRN...
AbstractRecent advances in high throughput sequencing technologies and concurrent refinements in 16S...
<div><p>Massively parallel high throughput sequencing technologies allow us to interrogate the micro...
To analyze complex biodiversity in microbial communities, 16S rRNA marker gene sequences are often a...
Massively parallel high throughput sequencing technologies allow us to interrogate the microbial com...
Abstract Background Species-level classification for 16S rRNA gene sequences remains a serious chall...
16S ribosomal RNA (rRNA) gene sequences are reliable markers for the taxonomic classification of mic...
Taxonomic classification of the thousands-millions of 16S rRNA gene sequences generated in microbiom...
rRNA-genes for phylogenetic classifications started to be used in 1980s first time by Carl Woese whi...
Naive Bayes classifiers (NBC) have dominated the field of taxonomic classification of amplicon seque...
Background: The need for precise and stable taxonomic classification is highly relevant in modern mi...
MotivationCombining a 16S rRNA (16S) gene database with metagenomic shotgun sequences promises unbia...
<p>Background: Current sequencing technology enables taxonomic profiling of microbial ecosystems at ...
Background: A 16S rRNA sequence represents a marker gene commonly used for taxonomic annotation of b...
Background: An open challenge in translational bioinformatics is the analysis of sequenced metagenom...
<div><p>The diversity of microbial species in a metagenomic study is commonly assessed using 16S rRN...
AbstractRecent advances in high throughput sequencing technologies and concurrent refinements in 16S...
<div><p>Massively parallel high throughput sequencing technologies allow us to interrogate the micro...
To analyze complex biodiversity in microbial communities, 16S rRNA marker gene sequences are often a...
Massively parallel high throughput sequencing technologies allow us to interrogate the microbial com...
Abstract Background Species-level classification for 16S rRNA gene sequences remains a serious chall...
16S ribosomal RNA (rRNA) gene sequences are reliable markers for the taxonomic classification of mic...
Taxonomic classification of the thousands-millions of 16S rRNA gene sequences generated in microbiom...
rRNA-genes for phylogenetic classifications started to be used in 1980s first time by Carl Woese whi...
Naive Bayes classifiers (NBC) have dominated the field of taxonomic classification of amplicon seque...
Background: The need for precise and stable taxonomic classification is highly relevant in modern mi...
MotivationCombining a 16S rRNA (16S) gene database with metagenomic shotgun sequences promises unbia...
<p>Background: Current sequencing technology enables taxonomic profiling of microbial ecosystems at ...
Background: A 16S rRNA sequence represents a marker gene commonly used for taxonomic annotation of b...
Background: An open challenge in translational bioinformatics is the analysis of sequenced metagenom...