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Bioinformatics
April 2005
Center for Biological Sequence Analysis, BioCentrum-DTU Building 208 Technical University of Denmark, DK-2800 Lyngby, Denmark.
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.
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