1. The Phenotype and Genotype Experiment Object Model (PaGE-OM): A Robust Data Structure for Information Related to DNA Variation
- Author
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Toshio Kojima, Yasumasa Shigemoto, Martin Senger, Atsuhiro Mukaiyama, Takeshi Tomiki, Matthew Darlison, Mark Woon, Hideaki Sugawara, Haseena Rajeevan, Akihiko Konagaya, Heikki Lehväslaiho, Kimitoshi Naito, Hiroshi Mizushima, David Fredman, Gudmundur A. Thorisson, Juha Muilu, Takashige Oroguchi, Masako Kuroda, Debasis Dash, Ituro Inoue, Albert V. Smith, and Anthony J. Brookes
- Subjects
Genotype ,Population ,Robust statistics ,Genomics ,Biology ,computer.software_genre ,03 medical and health sciences ,0302 clinical medicine ,Text mining ,Experiment Object ,Databases, Genetic ,Genetics ,Humans ,education ,Genetics (clinical) ,030304 developmental biology ,0303 health sciences ,education.field_of_study ,Models, Genetic ,business.industry ,Genetic Variation ,DNA ,Phenotype ,Data model ,Artificial intelligence ,business ,computer ,030217 neurology & neurosurgery ,Natural language processing - Abstract
Torrents of genotype-phenotype data are being generated, all of which must be captured, processed, integrated, and exploited. To do this optimally requires the use of standard and interoperable "object models," providing a description of how to partition the total spectrum of information being dealt with into elemental "objects" (such as "alleles," "genotypes," "phenotype values," "methods") with precisely stated logical interrelationships (such as "A objects are made up from one or more B objects"). We herein propose the Phenotype and Genotype Experiment Object Model (PaGE-OM; www.pageom.org), which has been tested and implemented in conjunction with several major databases, and approved as a standard by the Object Management Group (OMG). PaGE-OM is open-source, ready for use by the wider community, and can be further developed as needs arise. It will help to improve information management, assist data integration, and simplify the task of informatics resource design and construction for genotype and phenotype data projects.
- Published
- 2009
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