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Plant Bioinformatics

Overview of attention for book
Cover of 'Plant Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Using GenBank.
  3. Altmetric Badge
    Chapter 2 UniProtKB/Swiss-Prot, the Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View.
  4. Altmetric Badge
    Chapter 3 KEGG Bioinformatics Resource for Plant Genomics and Metabolomics.
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    Chapter 4 Plant Bioinformatics
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    Chapter 5 The Plant Ontology: A Tool for Plant Genomics.
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    Chapter 6 Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomics Data.
  8. Altmetric Badge
    Chapter 7 Gramene: A Resource for Comparative Analysis of Plants Genomes and Pathways.
  9. Altmetric Badge
    Chapter 8 PGSB/MIPS Plant Genome Information Resources and Concepts for the Analysis of Complex Grass Genomes.
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    Chapter 9 MaizeGDB: The Maize Genetics and Genomics Database.
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    Chapter 10 WheatGenome.info: A Resource for Wheat Genomics Resource.
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    Chapter 11 User Guidelines for the Brassica Database: BRAD.
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    Chapter 12 TAG Sequence Identification of Genomic Regions Using TAGdb.
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    Chapter 13 Short Read Alignment Using SOAP2.
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    Chapter 14 Tablet: Visualizing Next-Generation Sequence Assemblies and Mappings.
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    Chapter 15 Analysis of Genotyping-by-Sequencing (GBS) Data.
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    Chapter 16 Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions, and Improve Genome Assemblies.
  18. Altmetric Badge
    Chapter 17 Finding and Characterizing Repeats in Plant Genomes.
  19. Altmetric Badge
    Chapter 18 Analysis of RNA-Seq Data Using TopHat and Cufflinks.
Attention for Chapter 15: Analysis of Genotyping-by-Sequencing (GBS) Data.
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Chapter title
Analysis of Genotyping-by-Sequencing (GBS) Data.
Chapter number 15
Book title
Plant Bioinformatics
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3167-5_15
Pubmed ID
Book ISBNs
978-1-4939-3166-8, 978-1-4939-3167-5
Authors

Kagale, Sateesh, Koh, Chushin, Clarke, Wayne E, Bollina, Venkatesh, Parkin, Isobel A P, Sharpe, Andrew G, Sateesh Kagale, Chushin Koh, Wayne E. Clarke, Venkatesh Bollina, Isobel A. P. Parkin, Andrew G. Sharpe

Editors

David Edwards

Abstract

The development of genotyping-by-sequencing (GBS) to rapidly detect nucleotide variation at the whole genome level, in many individuals simultaneously, has provided a transformative genetic profiling technique. GBS can be carried out in species with or without reference genome sequences yields huge amounts of potentially informative data. One limitation with the approach is the paucity of tools to transform the raw data into a format that can be easily interrogated at the genetic level. In this chapter we describe bioinformatics tools developed to address this shortfall together with experimental design considerations to fully leverage the power of GBS for genetic analysis.

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X Demographics

The data shown below were collected from the profiles of 4 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
United States 1 1%
France 1 1%
Brazil 1 1%
Unknown 65 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 23%
Student > Ph. D. Student 15 22%
Student > Master 11 16%
Student > Bachelor 7 10%
Student > Doctoral Student 5 7%
Other 6 9%
Unknown 9 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 52%
Biochemistry, Genetics and Molecular Biology 13 19%
Computer Science 3 4%
Environmental Science 2 3%
Chemistry 2 3%
Other 1 1%
Unknown 12 17%
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 19 September 2016.
All research outputs
#13,215,982
of 22,831,537 outputs
Outputs from Methods in molecular biology
#3,464
of 13,126 outputs
Outputs of similar age
#184,612
of 393,555 outputs
Outputs of similar age from Methods in molecular biology
#328
of 1,470 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,126 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 72% 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 393,555 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 52% of its contemporaries.
We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.