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Plant Genomics Databases

Overview of attention for book
Cover of 'Plant Genomics Databases'

Table of Contents

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    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.
  19. Altmetric Badge
    Chapter 18 Plant Promoter Database (PPDB).
  20. Altmetric Badge
    Chapter 19 Construction of the Leaf Senescence Database and Functional Assessment of Senescence-Associated Genes.
Attention for Chapter 17: Variant Effect Prediction Analysis Using Resources Available at Gramene Database.
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Chapter title
Variant Effect Prediction Analysis Using Resources Available at Gramene Database.
Chapter number 17
Book title
Plant Genomics Databases
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6658-5_17
Pubmed ID
Book ISBNs
978-1-4939-6656-1, 978-1-4939-6658-5
Authors

Sushma Naithani, Matthew Geniza, Pankaj Jaiswal

Editors

Aalt D.J van Dijk

Abstract

The goal of Gramene database ( www.gramene.org ) is to empower the plant research community in conducting comparative genomics studies across model plants and crops by employing a phylogenetic framework and orthology-based projections. Gramene database (release #49) provides resources for comparative plant genomics including well-annotated plant genomes (39 complete reference genomes and six partial genomes), genetic or structural variation data for 14 plant species, pathways for 58 plant species, and gene expression data for 14 species including Arabidopsis, rice, maize, soybean, wheat, etc. (fetched from EBI-EMBL Gene Expression Atlas database). Gramene also facilitates visualization and analysis of user-defined data in the context of species-specific Genome Browsers or pathways. This chapter describes basic navigation for Gramene users and illustrates how they can use the genome section to analyze the gene expression and nucleotide variation data generated in their labs. This includes (1) upload and display of genomic data onto a Genome Browser track, (2) analysis of variation data using online Variant Effect Predictor (VEP) tool for smaller data sets, and (3) the use of the stand-alone Perl scripts and command line protocols for variant effect prediction on larger data sets.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Professor > Associate Professor 1 11%
Researcher 1 11%
Student > Master 1 11%
Unknown 4 44%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 22%
Mathematics 1 11%
Psychology 1 11%
Engineering 1 11%
Unknown 4 44%
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 30 January 2018.
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#15,404,272
of 22,914,829 outputs
Outputs from Methods in molecular biology
#5,360
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Outputs of similar age
#256,369
of 420,479 outputs
Outputs of similar age from Methods in molecular biology
#466
of 1,074 outputs
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