NetAcet: prediction of N-terminal acetylation sites

  • Authors:

  • Lars Kiemer;Jannick Dyrløv Bendtsen;Nikolaj Blom

  • Affiliations:

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

  • Venue:
  • Bioinformatics
  • Year:
  • 2005

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Abstract

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