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Plant Genomics Databases

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Cover of 'Plant Genomics Databases'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomic Data.
  3. Altmetric Badge
    Chapter 2 PGSB/MIPS PlantsDB Database Framework for the Integration and Analysis of Plant Genome Data.
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    Chapter 3 Plant Genome DataBase Japan (PGDBj).
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    Chapter 4 FLAGdb(++): A Bioinformatic Environment to Study and Compare Plant Genomes.
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    Chapter 5 Mining Plant Genomic and Genetic Data Using the GnpIS Information System.
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    Chapter 6 The Bio-Analytic Resource for Plant Biology.
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    Chapter 7 The Evolution of Soybean Knowledge Base (SoyKB).
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    Chapter 8 Using TropGeneDB: A Database Containing Data on Molecular Markers, QTLs, Maps, Genotypes, and Phenotypes for Tropical Crops.
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    Chapter 9 Species-Specific Genome Sequence Databases: A Practical Review.
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    Chapter 10 A Guide to the PLAZA 3.0 Plant Comparative Genomic Database.
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    Chapter 11 Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.
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    Chapter 12 PlaNet: Comparative Co-Expression Network Analyses for Plants.
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    Chapter 13 Practical Utilization of OryzaExpress and Plant Omics Data Center Databases to Explore Gene Expression Networks in Oryza Sativa and Other Plant Species.
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    Chapter 14 Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases: FragariaCyc, a Case Study.
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    Chapter 15 CSGRqtl: A Comparative Quantitative Trait Locus Database for Saccharinae Grasses.
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    Chapter 16 Plant Genome Duplication Database.
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    Chapter 17 Variant Effect Prediction Analysis Using Resources Available at Gramene Database.
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    Chapter 18 Plant Promoter Database (PPDB).
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    Chapter 19 Construction of the Leaf Senescence Database and Functional Assessment of Senescence-Associated Genes.
Attention for Chapter 1: Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomic Data.
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Chapter title
Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomic Data.
Chapter number 1
Book title
Plant Genomics Databases
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6658-5_1
Pubmed ID
Book ISBNs
978-1-4939-6656-1, 978-1-4939-6658-5
Authors

Dan M. Bolser, Daniel M. Staines, Emily Perry, Paul J. Kersey

Editors

Aalt D.J van Dijk

Abstract

Ensembl Plants ( http://plants.ensembl.org ) is an integrative resource presenting genome-scale information for 39 sequenced plant species. Available data includes genome sequence, gene models, functional annotation, and polymorphic loci; for the latter, additional information including population structure, individual genotypes, linkage, and phenotype data is available for some species. Comparative data is also available, including genomic alignments and "gene trees," which show the inferred evolutionary history of each gene family represented in the resource. Access to the data is provided through a genome browser, which incorporates many specialist interfaces for different data types, through a variety of programmatic interfaces, and via a specialist data mining tool supporting rapid filtering and retrieval of bulk data. Genomic data from many non-plant species, including those of plant pathogens, pests, and pollinators, is also available via the same interfaces through other divisions of Ensembl.Ensembl Plants is updated 4-6 times a year and is developed in collaboration with our international partners in the Gramene ( http://www.gramene.org ) and transPLANT projects ( http://www.transplantdb.eu ).

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 21%
Student > Master 12 12%
Student > Bachelor 10 10%
Researcher 10 10%
Student > Doctoral Student 9 9%
Other 9 9%
Unknown 31 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 38%
Biochemistry, Genetics and Molecular Biology 10 10%
Computer Science 6 6%
Engineering 4 4%
Chemistry 2 2%
Other 6 6%
Unknown 35 34%