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Plant Bioinformatics

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Cover of 'Plant Bioinformatics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Using GenBank.
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    Chapter 2 UniProtKB/Swiss-Prot, the Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View.
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    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.
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    Chapter 7 Gramene: A Resource for Comparative Analysis of Plants Genomes and Pathways.
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    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.
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    Chapter 17 Finding and Characterizing Repeats in Plant Genomes.
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    Chapter 18 Analysis of RNA-Seq Data Using TopHat and Cufflinks.
Attention for Chapter 17: Finding and Characterizing Repeats in Plant Genomes.
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Chapter title
Finding and Characterizing Repeats in Plant Genomes.
Chapter number 17
Book title
Plant Bioinformatics
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3167-5_17
Pubmed ID
Book ISBNs
978-1-4939-3166-8, 978-1-4939-3167-5
Authors

Nicolas, Jacques, Peterlongo, Pierre, Tempel, Sébastien, Jacques Nicolas, Pierre Peterlongo, Sébastien Tempel

Editors

David Edwards

Abstract

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of available software that can help biologists to look for these repeats and check some hypothetical models intended to characterize their structures. Since transposable elements are a major source of repeats in plants, many methods have been used or developed for this large class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided a whole section on this topic as well as a selection of the main existing software. In order to better understand how they work and how repeats may be efficiently found in genomes, it is necessary to look at the technical issues involved in the large-scale search of these structures. Indeed, it may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of the search for repeats and more complex patterns. The second section introduces the key concepts that are useful for understanding the current state of the art in playing with words, applied to genomic sequences. This can be seen as the first stage of a very general approach called linguistic analysis that is interested in the analysis of natural or artificial texts. Words, the lexical level, correspond to simple repeated entities in texts or strings. In fact, biologists need to represent more complex entities where a repeat family is built on more abstract structures, including direct or inverted small repeats, motifs, composition constraints as well as ordering and distance constraints between these elementary blocks. In terms of linguistics, this corresponds to the syntactic level of a language. The last section introduces concepts and practical tools that can be used to reach this syntactic level in biological sequence analysis.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 31%
Student > Bachelor 3 12%
Student > Master 3 12%
Student > Ph. D. Student 2 8%
Student > Postgraduate 2 8%
Other 2 8%
Unknown 6 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 31%
Agricultural and Biological Sciences 7 27%
Computer Science 2 8%
Linguistics 1 4%
Mathematics 1 4%
Other 1 4%
Unknown 6 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 01 November 2015.
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#20,295,099
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Outputs from Methods in molecular biology
#9,917
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#330,605
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Outputs of similar age from Methods in molecular biology
#1,053
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