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Bioinformatics Advance Access published online on November 11, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti130
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received September 1, 2004
Accepted October 28, 2004

Applications note

NetAcet: prediction of N-terminal acetylation sites

Lars Kiemer 1, Jannick Dyrløv Bendtsen 1, and Nikolaj Blom 1*

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

* To whom correspondence should be addressed.
Nikolaj Blom, E-mail: nikob{at}cbs.dtu.dk


  Abstract

Summary: We present here a neural network based method for prediction of amino-terminal acetylation -- by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast data set 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 other eukaryotic NatA orthologs.

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

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


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