Literature DB >> 19479963

The phenotype and genotype experiment object model (PaGE-OM): a robust data structure for information related to DNA variation.

Anthony J Brookes1, Heikki Lehvaslaiho, Juha Muilu, Yasumasa Shigemoto, Takashige Oroguchi, Takeshi Tomiki, Atsuhiro Mukaiyama, Akihiko Konagaya, Toshio Kojima, Ituro Inoue, Masako Kuroda, Hiroshi Mizushima, Gudmundur A Thorisson, Debasis Dash, Haseena Rajeevan, Matthew W Darlison, Mark Woon, David Fredman, Albert V Smith, Martin Senger, Kimitoshi Naito, Hideaki Sugawara.   

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.

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Year:  2009        PMID: 19479963     DOI: 10.1002/humu.20973

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  6 in total

Review 1.  Genotype-phenotype databases: challenges and solutions for the post-genomic era.

Authors:  Gudmundur A Thorisson; Juha Muilu; Anthony J Brookes
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

2.  Clarity and claims in variation/mutation databasing.

Authors:  Raymond Dalgleish; William S Oetting; Arleen D Auerbach; Jacques S Beckmann; Anne Cambon-Thomsen; Andrew Devereau; Marc S Greenblatt; George P Patrinos; Graham R Taylor; Mauno Vihinen; Anthony J Brookes
Journal:  Nat Biotechnol       Date:  2011-09-08       Impact factor: 54.908

Review 3.  Data standards for Omics data: the basis of data sharing and reuse.

Authors:  Stephen A Chervitz; Eric W Deutsch; Dawn Field; Helen Parkinson; John Quackenbush; Phillipe Rocca-Serra; Susanna-Assunta Sansone; Christian J Stoeckert; Chris F Taylor; Ronald Taylor; Catherine A Ball
Journal:  Methods Mol Biol       Date:  2011

4.  VarioML framework for comprehensive variation data representation and exchange.

Authors:  Myles Byrne; Ivo Fac Fokkema; Owen Lancaster; Tomasz Adamusiak; Anni Ahonen-Bishopp; David Atlan; Christophe Béroud; Michael Cornell; Raymond Dalgleish; Andrew Devereau; George P Patrinos; Morris A Swertz; Peter Em Taschner; Gudmundur A Thorisson; Mauno Vihinen; Anthony J Brookes; Juha Muilu
Journal:  BMC Bioinformatics       Date:  2012-10-03       Impact factor: 3.169

5.  Knowledge management for systems biology a general and visually driven framework applied to translational medicine.

Authors:  Dieter Maier; Wenzel Kalus; Martin Wolff; Susana G Kalko; Josep Roca; Igor Marin de Mas; Nil Turan; Marta Cascante; Francesco Falciani; Miguel Hernandez; Jordi Villà-Freixa; Sascha Losko
Journal:  BMC Syst Biol       Date:  2011-03-05

6.  FROG - Fingerprinting Genomic Variation Ontology.

Authors:  E Abinaya; Pankaj Narang; Anshu Bhardwaj
Journal:  PLoS One       Date:  2015-08-05       Impact factor: 3.240

  6 in total

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