VEuPathDB: The eukaryotic pathogen, vector and host bioinformatics resource center

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  • Beatrice Amos
  • Cristina Aurrecoechea
  • Matthieu Barba
  • Ana Barreto
  • Evelina Y. Basenko
  • Wojciech Bażant
  • Robert Belnap
  • Ann S. Blevins
  • Ulrike Böhme
  • John Brestelli
  • Brian P. Brunk
  • Mark Caddick
  • Danielle Callan
  • Lahcen Campbell
  • George K. Christophides
  • Kathryn Crouch
  • Kristina Davis
  • Jeremy Debarry
  • Ryan Doherty
  • Yikun Duan
  • Michael Dunn
  • Dave Falke
  • Steve Fisher
  • Paul Flicek
  • Brett Fox
  • Bindu Gajria
  • Gloria I. Giraldo-Calderón
  • Omar S. Harb
  • Elizabeth Harper
  • Christiane Hertz-Fowler
  • Mark J. Hickman
  • Connor Howington
  • Sufen Hu
  • Jay Humphrey
  • John Iodice
  • Andrew Jones
  • John Judkins
  • Sarah A. Kelly
  • Jessica C. Kissinger
  • Dae Kun Kwon
  • Kristopher Lamoureux
  • Daniel Lawson
  • Wei Li
  • Kallie Lies
  • Disha Lodha
  • Jamie Long
  • Robert M. MacCallum
  • Gareth Maslen
  • Mary Ann McDowell
  • Jaroslaw Nabrzyski
  • David S. Roos
  • Samuel S.C. Rund
  • Stephanie Wever Schulman
  • Achchuthan Shanmugasundram
  • Vasily Sitnik
  • Drew Spruill
  • David Starns
  • Christian J. Stoeckert
  • Sheena Shah Tomko
  • Haiming Wang
  • Susanne Warrenfeltz
  • Robert Wieck
  • Paul A. Wilkinson
  • Lin Xu
  • Jie Zheng

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports >500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate >1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial & Viral BRC.

Original languageEnglish
JournalNucleic Acids Research
Volume50
Issue numberD1
Number of pages14
ISSN0305-1048
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.

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