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Open Access Correction

Correction: Splice site identification using probabilistic parameters and SVM classification

AKMA Baten*, BCH Chang, SK Halgamuge and Jason Li

Author Affiliations

Dynamic Systems and Control Research Group, DoMME, The University of Melbourne, Victoria 3010, Australia

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BMC Bioinformatics 2007, 8:241  doi:10.1186/1471-2105-8-241

Published: 5 July 2007

First paragraph (this article has no abstract)

We proposed a method for the identification of splice sites [1] and it was tested against two data sets – DGSplicer (402695 acceptor and 285451 donor sites) and NN269 (6876 acceptor and 6316 donor sites).