| Title:
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NetAcet: prediction of N-terminal acetylation sites |
| Type:
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Journal articleJournal article |
| Participant(s):
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Technical University of Denmark
Technical University of Denmark
Technical University of Denmark
Email:
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| Abstract:
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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. |
| Published:
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in journal: Bioinformatics (ISSN: 1367-4803), vol: 21, issue: 7, pages: 1269-1270, 2005 |
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