Results 21 to 30 of about 129,780 (292)

Inference-based accuracy of metagenome prediction tools varies across sample types and functional categories

Microbiome, 2020
Background Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing.
Shan Sun, Roshonda B. Jones, Anthony A. Fodor   +2 more
doaj   +1 more source

MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities [PDF]

PeerJ, 2015
Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions.
Dongwan D. Kang, Jeff Froula, Rob Egan, Zhong Wang   +3 more
doaj   +2 more sources

metagenome-atlas/atlas: Bug fixes Drep

, 2021
ATLAS - Three commands to start analyzing your metagenome ...
Silas Kieser, Jackson M. Tsuji, Richard Allen White III, Christopher Bottoms, Joe Brown, Sean M. Colby, Vladimir Mikryukov, wangzc, Chris Overall, Mattias de Hollander, C. Titus Brown, Colin Brislawn   +11 more
core   +1 more source

Bacterial tag encoded FLX titanium amplicon pyrosequencing (bTEFAP) based assessment of prokaryotic diversity in metagenome of Lonar soda lake, India

Genomics Data, 2015
Bacterial diversity and archaeal diversity in metagenome of the Lonar soda lake sediment were assessed by bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP).
Pravin Dudhagara, Anjana Ghelani, Rajesh Patel, Rajesh Chaudhari, Shreyas Bhatt   +4 more
doaj   +1 more source

Evaluating the number of different genomes in a metagenome by means of the compositional spectra approach.

PLoS ONE, 2020
Determination of metagenome composition is still one of the most interesting problems of bioinformatics. It involves a wide range of mathematical methods, from probabilistic models of combinatorics to cluster analysis and pattern recognition techniques ...
Valery Kirzhner, Dvora Toledano-Kitai, Zeev Volkovich   +2 more
doaj   +1 more source

A Primer on Metagenomics

PLoS Computational Biology, 2010
Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world.
Bourne, Philip E., Wooley, John C., Godzik, Adam, Friedberg, Iddo   +3 more
openaire   +6 more sources

metagenome-atlas/atlas: GTDB v 207 low memory profiling

, 2022
New Features GTDB version 207 Low memory taxonomic annotation Minor changes Fix Typos by @roshni-b in https://github.com/metagenome-atlas/atlas/pull/520 Speed up DRAM annotations by @jmtsuji in https://github.com/metagenome-atlas/atlas/pull/534 Full ...
Silas Kieser, Richard Allen White III, Joe Brown, Vladimir Mikryukov, Roshni Biswas, Yan Hui, Jackson M. Tsuji, Christopher Bottoms, Cedric Midoux, Jie Zhu, Sean M. Colby, wangzc, Chris Overall, Mattias de Hollander, C. Titus Brown, Colin Brislawn   +15 more
core   +1 more source

RNA sequencing dataset characterizing transcriptomic responses to dietary changes in Caenorhabditis elegans

Data in Brief, 2019
Transcriptome analysis using next generation sequencing (NGS) technology provides the capability to understand global changes in gene expression throughout a range of tissue samples. The nematode Caenorhabditis elegans (C.
Scott T. Schumacker, Chloe A.M. Chidester, Raymond A. Enke, Matthew R. Marcello   +3 more
doaj   +1 more source

Metagenome sequencing and 768 microbial genomes from cold seep in South China Sea

Scientific Data, 2022
Measurement(s) metagenome assembled genomes Technology Type(s) metagenome sequencing and genome binning Sample Characteristic - Organism microorganism Sample Characteristic - Environment marine cold seep biome Sample Characteristic - Location South China
Huan Zhang, Minxiao Wang, Hao Wang, Hao Chen, Lei Cao, Zhaoshan Zhong, Chao Lian, Li Zhou, Chaolun Li   +8 more
doaj   +1 more source

Metagenomic sequence of saline desert microbiota from wild ass sanctuary, Little Rann of Kutch, Gujarat, India

Genomics Data, 2015
We report Metagenome from the saline desert soil sample of Little Rann of Kutch, Gujarat State, India. Metagenome consisted of 633,760 sequences with size 141,307,202 bp and 56% G + C content.
Rajesh Patel, Vishal Mevada, Dhaval Prajapati, Pravin Dudhagara, Prakash Koringa, C.G. Joshi   +5 more
doaj   +1 more source