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Bioinformatics Advance Access originally published online on November 11, 2004
Bioinformatics 2005 21(7):1269-1270; doi:10.1093/bioinformatics/bti130
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© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

NetAcet: prediction of N-terminal acetylation sites

Lars Kiemer , Jannick Dyrløv Bendtsen and Nikolaj Blom *

Center for Biological Sequence Analysis, BioCentrum-DTU Building 208 Technical University of Denmark DK-2800 Lyngby, Denmark

*To whom correspondence should be addressed.

Summary: We present here a neural network based method for prediction of N-terminal acetylation—by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N-acetylation for which most examples are known and for which orthologs have been found in several eukaryotes. We obtain correlation coefficients close to 0.7 on yeast data and a sensitivity up to 74% on mammalian data, suggesting that the method is valid for eukaryotic NatA orthologs.

Availability: The NetAcet prediction method is available as a public web server at http://www.cbs.dtu.dk/services/NetAcet/

Contact: nikob{at}cbs.dtu.dk

Supplementary information: http://www.cbs.dtu.dk/services/NetAcet/


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