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Microbial Environmental Genomics (MEG)

Overview of attention for book
Cover of 'Microbial Environmental Genomics (MEG)'

Table of Contents

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    Book Overview
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    Chapter 1 "Deciphering Archaeal Communities" Omics Tools in the Study of Archaeal Communities.
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    Chapter 2 Investigating the Endobacteria Which Thrive in Arbuscular Mycorrhizal Fungi
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    Chapter 3 GenoSol Platform: A Logistic and Technical Platform for Conserving and Exploring Soil Microbial Diversity.
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    Chapter 4 Sample Preparation for Fungal Community Analysis by High-Throughput Sequencing of Barcode Amplicons
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    Chapter 5 Fungal Communities in Soils: Soil Organic Matter Degradation.
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    Chapter 6 DNA-Based Characterization and Identification of Arbuscular Mycorrhizal Fungi Species.
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    Chapter 7 Molecular Identification of Soil Eukaryotes and Focused Approaches Targeting Protist and Faunal Groups Using High-Throughput Metabarcoding.
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    Chapter 8 Identification and In Situ Distribution of a Fungal Gene Marker: The Mating Type Genes of the Black Truffle
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    Chapter 9 Stable-Isotope Probing RNA to Study Plant/Fungus Interactions
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    Chapter 10 Targeted Gene Capture by Hybridization to Illuminate Ecosystem Functioning.
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    Chapter 11 Hybridization of Environmental Microbial Community Nucleic Acids by GeoChip.
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    Chapter 12 Reconstruction of Transformation Processes Catalyzed by the Soil Microbiome Using Metagenomic Approaches.
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    Chapter 13 MG-RAST, a Metagenomics Service for Analysis of Microbial Community Structure and Function.
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    Chapter 14 Analysis of Active Methylotrophic Communities: When DNA-SIP Meets High-Throughput Technologies.
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    Chapter 15 Functional Metagenomics: Construction and High-Throughput Screening of Fosmid Libraries for Discovery of Novel Carbohydrate-Active Enzymes.
  17. Altmetric Badge
    Chapter 16 Metatranscriptomics of Soil Eukaryotic Communities
  18. Altmetric Badge
    Chapter 17 Analysis of Ancient DNA in Microbial Ecology.
Attention for Chapter 12: Reconstruction of Transformation Processes Catalyzed by the Soil Microbiome Using Metagenomic Approaches.
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Chapter title
Reconstruction of Transformation Processes Catalyzed by the Soil Microbiome Using Metagenomic Approaches.
Chapter number 12
Book title
Microbial Environmental Genomics (MEG)
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3369-3_12
Pubmed ID
Book ISBNs
978-1-4939-3367-9, 978-1-4939-3369-3
Authors

Schöler, Anne, de Vries, Maria, Vestergaard, Gisle, Schloter, Michael, Anne Schöler, Maria de Vries, Gisle Vestergaard, Michael Schloter

Editors

Francis Martin, Stephane Uroz

Abstract

Microorganisms are central players in the turnover of nutrients in soil and drive the decomposition of complex organic materials into simpler forms that can be utilized by other biota. Therefore microbes strongly drive soil quality and ecosystem services provided by soils, including plant yield and quality. Thus it is one of the major goals of soil sciences to describe the most relevant enzymes that are involved in nutrient mobilization and to understand the regulation of gene expression of the corresponding genes. This task is however impeded by the enormous microbial diversity in soils. Indeed, we are far to appreciate the number of species present in 1 g of soil, as well as the major functional traits they carry. Here, also most next-generation sequencing (NGS) approaches fail as immense sequencing efforts are needed to fully uncover the functional diversity of soils. Thus even if a gene of interest can be identified by BLAST similarity analysis, the obtained number of reads by NGS is too low for a quantitative assessment of the gene or for a description of its taxonomic diversity. Here we present an integrated approach, which we termed the second-generation full cycle approach, to quantify the abundance and diversity of key enzymes involved in nutrient mobilization. This approach involves the functional annotation of metagenomic data with a relative low coverage (5 Gbases or less) and the design of highly targeted primer systems to assess the abundance or diversity of enzyme-coding genes that are drivers for a particular transformation step in nutrient turnover.

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X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 7%
France 1 3%
Unknown 26 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 24%
Researcher 5 17%
Student > Bachelor 4 14%
Student > Doctoral Student 2 7%
Student > Ph. D. Student 2 7%
Other 4 14%
Unknown 5 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 31%
Biochemistry, Genetics and Molecular Biology 7 24%
Immunology and Microbiology 2 7%
Earth and Planetary Sciences 2 7%
Environmental Science 1 3%
Other 1 3%
Unknown 7 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 January 2016.
All research outputs
#13,339,171
of 23,498,099 outputs
Outputs from Methods in molecular biology
#3,425
of 13,368 outputs
Outputs of similar age
#183,454
of 396,908 outputs
Outputs of similar age from Methods in molecular biology
#324
of 1,472 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,368 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 396,908 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 1,472 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.