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The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science
Author(s) -
Richard Bruskiewich,
Martin Senger,
Guy Davenport,
Manuel Ruíz,
Mathieu Rouard,
Tom Hazekamp,
Masaru Takeya,
Koji Doi,
Kouji Satoh,
Marcos Mota do Carmo Costa,
Reinhard Simon,
Jayashree Balaji,
Akinnola N. 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 Ruiz Rojas,
N. F. Martins,
Γεώργιος Παππάς,
Ryan Alamban,
Roque Almodiel,
Lord Hendrix Barboza,
Jeffrey Detras,
Kevin Manansala,
Michael J. Mendoza,
Jeffrey Morales,
Barry Peralta,
Rowena Valerio,
Yi Zhang,
Sergio Alonso y Gregorio,
Joseph Anthony C. Hermocilla,
Michael Echavez,
Jan Michael C. Yap,
Andrew Farmer,
Gary Schiltz,
Jennifer Lee,
Terry Casstevens,
Pankaj Jaiswal,
Ayton Meintjes,
Mark D. Wilkinson,
Benjamin M. Good,
James Wagner,
Jane Morris,
David Marshall,
Anthony Collins,
Shoshi Kikuchi,
Thomas Metz,
Graham McLaren,
T.J.L. van Hintum
Publication year - 2008
Publication title -
international journal of plant genomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 30
eISSN - 1687-5370
pISSN - 1687-5389
DOI - 10.1155/2008/369601
Subject(s) - interoperability , workbench , computer science , suite , ontology , middleware (distributed applications) , domain (mathematical analysis) , implementation , data science , world wide web , data access , database , software engineering , data mining , history , mathematical analysis , philosophy , mathematics , archaeology , epistemology , visualization
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.

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