4.5 Article

Tripal and Galaxy: supporting reproducible scientific workflows for community biological databases

出版社

OXFORD UNIV PRESS
DOI: 10.1093/database/baaa032

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资金

  1. US National Science Foundation (NSF) [1443040, 1444573]
  2. National Institute of Food and Agriculture [NRSP10]
  3. National Institute of Food and Agriculture project, Mcintire Stennis [WNP00009]
  4. National Institute of Food and Agriculture project, Hatch project [1014919]
  5. Division Of Integrative Organismal Systems
  6. Direct For Biological Sciences [1444573] Funding Source: National Science Foundation
  7. Office of Advanced Cyberinfrastructure (OAC)
  8. Direct For Computer & Info Scie & Enginr [1443040] Funding Source: National Science Foundation

向作者/读者索取更多资源

Online biological databases housing genomics, genetic and breeding data can be constructed using the Tripal toolkit. Tripal is an open-source, internationally developed framework that implements FAIR data principles and is meant to ease the burden of constructing such websites for research communities. Use of a common, open framework improves the sustainability and manageability of such as site. Site developers can create extensions for their site and in turn share those extensions with others. One challenge that community databases often face is the need to provide tools for their users that analyze increasingly larger datasets using multiple software tools strung together in a scientific workflow on complicated computational resources. The Tripal Galaxy module, a 'plug-in' for Tripal, meets this need through integration of Tripal with the Galaxy Project workflow management system. Site developers can create workflows appropriate to the needs of their community using Galaxy and then share those for execution on their Tripal sites via automatically constructed, but configurable, web forms or using an application programming interface to power web-based analytical applications. The Tripal Galaxy module helps reduce duplication of effort by allowing site developers to spend time constructing workflows and building their applications rather than rebuilding infrastructure for job management of multi-step applications.

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