The Generation Challenge Programme Platform: Semantic Standards andWorkbench for Crop Science

• Autor(a) principal: Bruskiewich, Richard
• Data de Publicação: 2008
• Outros Autores: Senger, Martin, Davenport, Guy, Ruiz, Manuel, Rouard, Mathieu, Hazekamp, Tom, Takeya, Masaru, Doi, Koji, Satoh, Kouji, Costa, Marcos, Simon, Reinhard, Balaji, Jayashree, Akintunde, Akinnola, Mauleon, Ramil, Wanchana, Samart, Shah, Trushar, Anacleto, Mylah, Portugal, Arllet, Ulat, Victor Jun, Thongjuea, Supat, Braak, Kyle, Ritter, Sebastian, Dereeper, Alexis, Skofic, Milko, Rojas, Edwin, Martins, Natalia, Pappas, Georgios, Alamban, Ryan, Almodiel, Roque, Barboza, Lord Hendrix, Detras, Jeffrey, Manansala, Kevin, Mendoza, Michael Jonathan, Morales, Jeffrey, Peralta, Barry, Valerio, Rowena, Zhang, Yi, Gregorio, Sergio, Hermocilla, Joseph, Echavez, Michael, Yap, Jan Michael, Farmer, Andrew, Schiltz, Gary, Lee, Jennifer, Casstevens, Terry, Jaiswa, Pankaj, Meintjes, Ayton, Wilkinson, Mark, Good, Benjamin, Wagner, James, Morris, Jane, Marshall, David, Collins, Anthony, Kikuchi, Shoshi, Metz, Thomas, McLaren, Graham, Hintum, Theo van
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UCB
• Texto Completo: http://twingo.ucb.br:8080/jspui/handle/10869/574; https://repositorio.ucb.br:9443/jspui/handle/123456789/7873
• topic: Bioinformatics; Comparative genomics; Genome annotation

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.