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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)
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    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
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    Chapter 18 Navigating the i5k Workspace@NAL: A Resource for Arthropod Genomes
Attention for Chapter 5: EuPathDB: The Eukaryotic Pathogen Genomics Database Resource
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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Chapter title
EuPathDB: The Eukaryotic Pathogen Genomics Database Resource
Chapter number 5
Book title
Eukaryotic Genomic Databases
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7737-6_5
Pubmed ID
Book ISBNs
978-1-4939-7736-9, 978-1-4939-7737-6

Susanne Warrenfeltz, Evelina Y. Basenko, Kathryn Crouch, Omar S. Harb, Jessica C. Kissinger, David S. Roos, Achchuthan Shanmugasundram, Fatima Silva-Franco, Warrenfeltz, Susanne, Basenko, Evelina Y., Crouch, Kathryn, Harb, Omar S., Kissinger, Jessica C., Roos, David S., Shanmugasundram, Achchuthan, Silva-Franco, Fatima


Fighting infections and developing novel drugs and vaccines requires advanced knowledge of pathogen's biology. Readily accessible genomic, functional genomic, and population data aids biological and translational discovery. The Eukaryotic Pathogen Database Resources ( http://eupathdb.org ) are data mining resources that support hypothesis driven research by facilitating the discovery of meaningful biological relationships from large volumes of data. The resource encompasses 13 sites that support over 170 species including pathogenic protists, oomycetes, and fungi as well as evolutionarily related nonpathogenic species. EuPathDB integrates preanalyzed data with advanced search capabilities, data visualization, analysis tools and a comprehensive record system in a graphical interface that does not require prior computational skills. This chapter describes guiding concepts common across EuPathDB sites and illustrates the powerful data mining capabilities of some of the available tools and features.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 16%
Student > Bachelor 7 11%
Researcher 6 10%
Student > Master 6 10%
Student > Doctoral Student 3 5%
Other 10 16%
Unknown 21 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 32%
Agricultural and Biological Sciences 10 16%
Computer Science 4 6%
Nursing and Health Professions 1 2%
Immunology and Microbiology 1 2%
Other 3 5%
Unknown 24 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 22 January 2019.
All research outputs
of 23,344,526 outputs
Outputs from Methods in molecular biology
of 13,338 outputs
Outputs of similar age
of 444,166 outputs
Outputs of similar age from Methods in molecular biology
of 1,502 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,338 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 92% 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 444,166 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 1,502 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.