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POEM, A 3-dimensional exon taxonomy and patterns in untranslated exons

Knapp, Keith, Chonka, Ashley and Chen, Yi-Peng Phoebe 2008, POEM, A 3-dimensional exon taxonomy and patterns in untranslated exons, BMC Genomics, vol. 9, no. 428, pp. 1-11.

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Title POEM, A 3-dimensional exon taxonomy and patterns in untranslated exons
Author(s) Knapp, Keith
Chonka, Ashley
Chen, Yi-Peng Phoebe
Journal name BMC Genomics
Volume number 9
Issue number 428
Start page 1
End page 11
Publisher BioMed Central Ltd
Place of publication London, England
Publication date 2008
ISSN 1471-2164
Summary Background: The existence of exons and introns has been known for thirty years. Despite this knowledge, there is a lack of formal research into the categorization of exons. Exon taxonomies used by researchers tend to be selected ad hoc or based on an information poor de-facto standard. Exons have been shown to have specific properties and functions based on among other things their location and order. These factors should play a role in the naming to increase specificity about which exon type(s) are in question.

Results: POEM (Protein Oriented Exon Monikers) is a new taxonomy focused on protein proximal exons. It integrates three dimensions of information (Global Position, Regional Position and Region), thus its exon categories are based on known statistical exon features. POEM is applied to two congruent untranslated exon datasets resulting in the following statistical properties. Using the POEM taxonomy previous wide ranging estimates of initial 5' untranslated region exons are resolved. According to our datasets, 29–36% of genes have wholly untranslated first exons. Untranslated exon containing sequences are shown to have consistently up to 6 times more 5' untranslated exons than 3' untranslated exons. Finally, three exon patterns are determined which account for 70% of untranslated exon genes.

Conclusion: We describe a thorough three-dimensional exon taxonomy called POEM, which is biologically and statistically relevant. No previous taxonomy provides such fine grained information and yet still includes all valid information dimensions. The use of POEM will improve the accuracy of genefinder comparisons and analysis by means of a common taxonomy. It will also facilitate unambiguous communication due to its fine granularity
Language eng
Field of Research 080301 Bioinformatics Software
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2008
Copyright notice ©2008, Knapp et al
Persistent URL http://hdl.handle.net/10536/DRO/DU:30017629

Document type: Journal Article
Collections: School of Engineering and Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.