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dc.contributor.authorBeisvag, Vidar
dc.contributor.authorKauffmann, Audrey
dc.contributor.authorMalone, James
dc.contributor.authorFoy, Carole
dc.contributor.authorSalit, Marc
dc.contributor.authorSchimmel, H
dc.contributor.authorBongcam-Rudloff, Eric
dc.contributor.authorLandegren, Ulf
dc.contributor.authorParkinson, Helen
dc.contributor.authorHuber, Wolfgang
dc.contributor.authorBrazma, Alvis
dc.contributor.authorSandvik, Arne Kristian
dc.contributor.authorKuiper, Martin
dc.date.accessioned2019-08-29T07:37:09Z
dc.date.available2019-08-29T07:37:09Z
dc.date.created2011-06-30T10:04:14Z
dc.date.issued2011
dc.identifier.citationBioTechniques. 2011, 50 (1), 27-31.nb_NO
dc.identifier.issn0736-6205
dc.identifier.urihttp://hdl.handle.net/11250/2611512
dc.description.abstractWhile minimum information about a microarray experiment (MIAME) standards have helped to increase the value of the microarray data deposited into public databases like ArrayExpress and Gene Expression Omnibus (GEO), limited means have been available to assess the quality of this data or to identify the procedures used to normalize and transform raw data. The EMERALD FP6 Coordination Action was designed to deliver approaches to assess and enhance the overall quality of microarray data and to disseminate these approaches to the microarray community through an extensive series of workshops, tutorials, and symposia. Tools were developed for assessing data quality and used to demonstrate how the removal of poor-quality data could improve the power of statistical analyses and facilitate analysis of multiple joint microarray data sets. These quality metrics tools have been disseminated through publications and through the software package arrayQualityMetrics. Within the framework provided by the Ontology of Biomedical Investigations, ontology was developed to describe data transformations, and software ontology was developed for gene expression analysis software. In addition, the consortium has advocated for the development and use of external reference standards in microarray hybridizations and created the Molecular Methods (MolMeth) database, which provides a central source for methods and protocols focusing on microarray-based technologies.nb_NO
dc.language.isoengnb_NO
dc.publisherFuture Medicinenb_NO
dc.relation.uriContributions of the EMERALD project to assessing and improving microarray data quality
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleContributions of the EMERALD project to assessing and improving microarray data qualitynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber27-31nb_NO
dc.source.volume50nb_NO
dc.source.journalBioTechniquesnb_NO
dc.source.issue1nb_NO
dc.identifier.doi10.2144/000113591
dc.identifier.cristin827673
dc.description.localcodeCreative Commons Attribution Non-Commercial No Derivatives Licensenb_NO
cristin.unitcode194,65,15,0
cristin.unitcode1920,15,0,0
cristin.unitcode194,66,10,0
cristin.unitnameInstitutt for klinisk og molekylær medisin
cristin.unitnameMedisinsk klinikk
cristin.unitnameInstitutt for biologi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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