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Eukaryotic Genomic Databases

Overview of attention for book
Cover of 'Eukaryotic Genomic Databases'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Identifying Sequenced Eukaryotic Genomes and Transcriptomes with diArk
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    Chapter 2 An Introduction to the Saccharomyces Genome Database (SGD)
  4. Altmetric Badge
    Chapter 3 Using the Candida Genome Database
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    Chapter 4 PomBase: The Scientific Resource for Fission Yeast
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    Chapter 5 EuPathDB: The Eukaryotic Pathogen Genomics Database Resource
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    Chapter 6 The Ensembl Genome Browser: Strategies for Accessing Eukaryotic Genome Data
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    Chapter 7 Mouse Genome Informatics (MGI) Is the International Resource for Information on the Laboratory Mouse
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    Chapter 8 A Primer for the Rat Genome Database (RGD)
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    Chapter 9 Bovine Genome Database: Tools for Mining the Bos taurus Genome
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    Chapter 10 Navigating Xenbase: An Integrated Xenopus Genomics and Gene Expression Database
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    Chapter 11 Using ZFIN: Data Types, Organization, and Retrieval
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    Chapter 12 EchinoBase: Tools for Echinoderm Genome Analyses
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    Chapter 13 A Multi-Omics Database for Parasitic Nematodes and Trematodes
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    Chapter 14 Using WormBase: A Genome Biology Resource for Caenorhabditis elegans and Related Nematodes
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    Chapter 15 Using WormBase ParaSite: An Integrated Platform for Exploring Helminth Genomic Data
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    Chapter 16 Using FlyBase to Find Functionally Related Drosophila Genes
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    Chapter 17 Hymenoptera Genome Database: Using HymenopteraMine to Enhance Genomic Studies of Hymenopteran Insects
  19. Altmetric Badge
    Chapter 18 Navigating the i5k Workspace@NAL: A Resource for Arthropod Genomes
Attention for Chapter 17: Hymenoptera Genome Database: Using HymenopteraMine to Enhance Genomic Studies of Hymenopteran Insects
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  • High Attention Score compared to outputs of the same age and source (84th percentile)

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Chapter title
Hymenoptera Genome Database: Using HymenopteraMine to Enhance Genomic Studies of Hymenopteran Insects
Chapter number 17
Book title
Eukaryotic Genomic Databases
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7737-6_17
Pubmed ID
Book ISBNs
978-1-4939-7736-9, 978-1-4939-7737-6
Authors

Christine G. Elsik, Aditi Tayal, Deepak R. Unni, Gregory W. Burns, Darren E. Hagen, Elsik, Christine G., Tayal, Aditi, Unni, Deepak R., Burns, Gregory W., Hagen, Darren E.

Abstract

The Hymenoptera Genome Database (HGD; http://hymenopteragenome.org ) is a genome informatics resource for insects of the order Hymenoptera, which includes bees, ants and wasps. HGD provides genome browsers with manual annotation tools (JBrowse/Apollo), BLAST, bulk data download, and a data mining warehouse (HymenopteraMine). This chapter focuses on the use of HymenopteraMine to create annotation data sets that can be exported for use in downstream analyses. HymenopteraMine leverages the InterMine platform to combine genome assemblies and official gene sets with data from OrthoDB, RefSeq, FlyBase, Gene Ontology, UniProt, InterPro, KEGG, Reactome, dbSNP, PubMed, and BioGrid, as well as precomputed gene expression information based on publicly available RNAseq. Built-in template queries provide starting points for data exploration, while the QueryBuilder tool supports construction of complex custom queries. The List Analysis and Genomic Regions search tools execute queries based on uploaded lists of identifiers and genome coordinates, respectively. HymenopteraMine facilitates cross-species data mining based on orthology and supports meta-analyses by tracking identifiers across gene sets and genome assemblies.

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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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 40%
Researcher 2 20%
Student > Bachelor 1 10%
Student > Postgraduate 1 10%
Unknown 2 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 40%
Agricultural and Biological Sciences 4 40%
Unknown 2 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 April 2021.
All research outputs
#7,310,340
of 23,054,359 outputs
Outputs from Methods in molecular biology
#2,223
of 13,196 outputs
Outputs of similar age
#148,049
of 442,464 outputs
Outputs of similar age from Methods in molecular biology
#214
of 1,499 outputs
Altmetric has tracked 23,054,359 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 13,196 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 82% 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 442,464 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 65% of its contemporaries.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.