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Wolverhampton Intellectual Repository and E-Theses > Research Institutes > Research Institute in Healthcare Science > Cancer Research Group > Assigning Level in Data-mining Exercises

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/29804
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Title: Assigning Level in Data-mining Exercises
Authors: Hooley, Paul
Chilton, Ian J.
Fincham, Daron A.
Burns, Alan T. H.
Whitehead, Michael P.
Citation: Bioscience Education Electronic Journal, 9: 1-9
Publisher: Centre for Bioscience, the Higher Education Academy
Journal: Bioscience Education Electronic Journal
Issue Date: 2007
URI: http://hdl.handle.net/2436/29804
DOI: doi:10.3108/beej.9.4
Additional Links: http://www.bioscience.heacademy.ac.uk/journal/vol9/beej-9-4.htm
Abstract: There is currently much interest in ascribing outcomes to Masters (M) level programmes. It is particularly difficult to define M level outcomes in bioinformatics for students on non-specialist programmes. An approach is described that attempts to discriminate undergraduate from M level in a data-mining exercise. Differentiation of level is based upon the taxonomic origin of a DNA sequence, the relative increase in gene complexity from lower to higher eukaryote and the initiative required to use a wider range of databases and analytical tools.
Type: Article
Language: en
Keywords: Masters Level
Higher education
Data mining
Bioinformatics
ISSN: 1479-7860
Appears in Collections: Cancer Research Group

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