Blomap: an encoding of amino acids which improves signal peptide cleavage site prediction

Maetschke, Stefan, Towsey, Michael W., & Boden, Mikael (2005) Blomap: an encoding of amino acids which improves signal peptide cleavage site prediction. In Chen, Yi-Ping Phoebe & Wong, Limsoon (Eds.) Third Asia Pacific Bioinformatics Conference, 2005, Singapore.


Research on cleavage site prediction for signal peptides has focused mainly on the application of different classification algorithms to achieve improved prediction accuracies. This paper addresses the fundamental issue of amino acid encoding to present amino acid sequences in the most beneficial way for machine learning algorithms. A comparison of several standard encoding methods shows, that for cleavage site prediction the frequently used orthonormal encoding is inferior compared to other methods. The best results are achieved with a new encoding method named BLOMAP – based on the BLOSUM62 substitution matrix – using a Naïve Bayes classifier.

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16 citations in Scopus
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233 since deposited on 14 May 2007
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ID Code: 7553
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
ISBN: 9781860944772
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2005 (please consult author)
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 14 May 2007 00:00
Last Modified: 29 Feb 2012 13:30

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