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The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

By Richard Bruskiewich, Martin Senger, Guy Davenport, Manuel Ruiz, Mathieu Rouard, Tom Hazekamp, Masaru Takeya, Koji Doi, Kouji Satoh, Marcos Costa, Reinhard Simon, Jayashree Balaji, Akinnola Akintunde, Ramil Mauleon, Samart Wanchana, Trushar Shah, Mylah Anacleto, Arllet Portugal, Victor Jun Ulat, Supat Thongjuea, Kyle Braak, Sebastian Ritter, Alexis Dereeper, Milko Skofic, Edwin Rojas, Natalia Martins, Georgios Pappas, Ryan Alamban, Roque Almodiel, Lord Hendrix Barboza, Jeffrey Detras, Kevin Manansala, Michael Jonathan Mendoza, Jeffrey Morales, Barry Peralta, Rowena Valerio, Yi Zhang, Sergio Gregorio, Joseph Hermocilla, Michael Echavez, Jan Michael Yap, Andrew Farmer, Gary Schiltz, Jennifer Lee, Terry Casstevens, Pankaj Jaiswal, Ayton Meintjes, Mark Wilkinson, Benjamin Good, James Wagner, Jane Morris, David Marshall, Anthony Collins, Shoshi Kikuchi, Thomas Metz, Graham McLaren and Theo van Hintum


The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making

Topics: Research Article
Publisher: Hindawi Publishing Corporation
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Provided by: PubMed Central

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