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Wolverhampton Intellectual Repository and E-Theses > Research Institutes > Research Institute in Healthcare Science > Cancer Research Group > Fungal gene sequences make excellent models for teaching data mining

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/29586
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Title: Fungal gene sequences make excellent models for teaching data mining
Authors: Hooley, Paul
Burns, Alan T. H.
Whitehead, Michael P.
Citation: Mycologist, 18(3): 118-124
Publisher: Elsevier Science Direct
Journal: Mycologist
Issue Date: 2004
URI: http://hdl.handle.net/2436/29586
DOI: 10.1017/S0269-915X(04)00304-0
Additional Links: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B7XMS-4R10WNS-5&_user=1644469&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000054077&_version=1&_urlVersion=0&_userid=1644469&md5=1530e2d002f11753de20b51bced8e4ce
Abstract: A brief introductory exercise in the use of on-line databases to examine fungal genes and their products is described. Fungal genes make particularly good teaching models owing to their relatively simple eukaryotic structure and wide range of homologues in higher organisms including humans. An evaluation of students' reactions to the exercise is included.
Type: Article
Language: en
Keywords: Data mining
BLAST
Fungal genes
Appears in Collections: Cancer Research Group

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