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NetAcet: prediction of N-terminal acetylation sites
2004
Bioinformatics
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We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant posttranslational 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
doi:10.1093/bioinformatics/bti130
pmid:15539450
fatcat:jtctp6ha2ndzvbxedlv4rwfqxy