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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:  [email protected]

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