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Workshop on laboratory protocol standards for the molecular methods database

Klingström, Tomas (author)
Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för husdjursgenetik (HGEN),Department of Animal Breeding and Genetics
Soldatova, Larissa (author)
Aberystwyth University, UK
Stevens, Robert (author)
Universtity of Manchester, UK
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Roos, Erik (author)
University of Groningen, The Netherlands
Swertz, Morris (author)
University of Groningen, The Netherlands
Müller, Kristian (author)
University of Potsdam, Germany
Kalas, Matus (author)
University of Bergen, Norway
Lambrix, Patrick (author)
Linköpings universitet,Databas och informationsteknik,Tekniska högskolan,IDA/ADIT
Taussig, Michael (author)
Babraham Bioscience Technologies, Cambridge, UK
Litton, Jan-Eric (author)
Karolinska Institutet,Karolinska Institutet, Stockholm, Sweden
Landegren, Ulf (author)
Uppsala universitet,Molekylära verktyg,Science for Life Laboratory, SciLifeLab,Uppsala University, Sweden
Bongcam Rudloff, Erik (author)
Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Uppsala universitet,Science for Life Laboratory, SciLifeLab,Molekylära verktyg,Swedish University of Agricultural Sciences and Uppsala University, Sweden,Institutionen för husdjursgenetik (HGEN),Department of Animal Breeding and Genetics,Uppsala University
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 (creator_code:org_t)
 
Elsevier BV, 2013
2013
English.
In: New Biotechnology. - : Elsevier BV. - 1871-6784 .- 1876-4347. ; 30:2, s. 109-113
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Management of data to produce scientific knowledge is a key challenge for biological research in the 21st century. Emerging high-throughput technologies allow life science researchers to produce big data at speeds and in amounts that were unthinkable just a few years ago. This places high demands on all aspects of the workflow: from data capture (including the experimental constraints of the experiment), analysis and preservation, to peer-reviewed publication of results. Failure to recognise the issues at each level can lead to serious conflicts and mistakes; research may then be compromised as a result of the publication of non-coherent protocols, or the misinterpretation of published data. In this report, we present the results from a workshop that was organised to create an ontological data-modelling framework for Laboratory Protocol Standards for the Molecular Methods Database (MolMeth). The workshop provided a set of short- and long-term goals for the MolMeth database, the most important being the decision to use the established EXACT description of biomedical ontologies as a starting point.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

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