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Workflow for Rapid Metagenome Analysis
2014Analyses of metagenomes in life sciences present new opportunities as well as challenges to the scientific community and call for advanced computational methods and workflows. The large amount of data collected from samples via next-generation sequencing (NGS) technologies render manual approaches to sequence comparison and annotation unsuitable ...
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In Silico Metagenomics Analysis
2021The field of metagenomics (study of a system’s microbiome) comes with various questions researchers are called to answer. Questions about the microbiota’s identity, the interactions of the participating bacteria, fungi, and viruses and their associations with health and disease.
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Advances in computational analysis of metagenome sequences
Environmental Microbiology, 2012Summary Second‐generation sequencing technologies are revolutionizing the study of metagenomes. Whole‐genome shotgun sequencing of metagenomic DNA may become an attractive alternative to the current widely used ribosomal RNA gene studies.
Colin F, Davenport, Burkhard, Tümmler
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2011
Improved sampling of diverse environments and advances in the development and application of next-generation sequencing technologies are accelerating the rate at which new metagenomes are produced. Over the past few years, the major challenge associated with metagenomics has shifted from generating to analyzing sequences.
Elizabeth M. Glass, Folker Meyer
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Improved sampling of diverse environments and advances in the development and application of next-generation sequencing technologies are accelerating the rate at which new metagenomes are produced. Over the past few years, the major challenge associated with metagenomics has shifted from generating to analyzing sequences.
Elizabeth M. Glass, Folker Meyer
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METHODS OF METAGENOMIC ANALYSIS
МИКРОБИОЛОГИЯ ЖӘНЕ ВИРУСОЛОГИЯMetagenomic analysis is a powerful tool for studying the genetic diversity of microorganisms that inhabit different ecological niches. Modern methods of sequencing and bioinformatics analysis allow us to study the taxonomic composition, functional features, and evolutionary patterns of microbial communities without the need for cultivation.
O.N. REVA +5 more
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2014
In this chapter, we first briefly introduce the background of next-generation sequencing metagenomics, including the special properties in this research field and the challenges for statistical analysis. A metagenomic study typically consists of sampling, filtering, DNA extraction, sequencing, binning, assembly, profiling and down-stream analysis.
Ruofei Du, Zhide Fang
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In this chapter, we first briefly introduce the background of next-generation sequencing metagenomics, including the special properties in this research field and the challenges for statistical analysis. A metagenomic study typically consists of sampling, filtering, DNA extraction, sequencing, binning, assembly, profiling and down-stream analysis.
Ruofei Du, Zhide Fang
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Metagenomic Analysis of Isotopically Enriched DNA
2010This detailed protocol describes an approach for combining DNA stable-isotope probing-based enrichment, multiple displacement amplification (MDA), and metagenomics. Together, these three methodologies enable selective access to the genomes of uncultivated organisms that actively grow using isotopically labelled carbon and nitrogen sources.
Yin, Chen +4 more
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Metagenomic Analysis of Intestinal Microbiomes in Chickens
2011The digestive tract of animals contains a very large numbers of microorganisms with a high diversity. Traditionally, characterization of these microbial communities has relied on the ability to clonally culture each microorganism. With significant improvements in nucleotide sequencing technologies to economically obtain billions of bases, the study of ...
Taejoong, Kim, Egbert, Mundt
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An Extensible Framework for Genomic and Metagenomic Analysis
2014Computational tools for supporting the management of scientific experiments are fundamental for the modern science. These tools must be easy to use, extensible and robust. This paper presents a framework for managing bioinformatics’ experiments, focusing on analysis of genomic and metagenomic data.
Luciano A. Digiampietri +5 more
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2019
In this chapter, we learn how to use the metagenomeSeq in the R package for both metadata and functional analyses of metagenomes using published data. It includes preprocessing and annotation methods such as gene-centered, pathway-centered, and functional diversity analyses.
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In this chapter, we learn how to use the metagenomeSeq in the R package for both metadata and functional analyses of metagenomes using published data. It includes preprocessing and annotation methods such as gene-centered, pathway-centered, and functional diversity analyses.
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