Machine Learning Prediction of Amino Acid Patterns in Protein N-myristoylation

  • Ryo Okada
  • Manabu Sugii
  • Hiroshi Matsuno
  • Satoru Miyano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4146)


Protein N-myristoylation is the lipid modification in which the 14-carbon saturated fatty acid binds covalently to N-terminal of virus-based and eukaryotic protein. In this study, we suggest an approach to predict the pattern of N-myristoylation signal using the machine learning system BONSAI. BONSAI finds rules in combination of an alphabet indexings and decision trees. Computational experiments with BONSAI classified amino acid residues depending on effect for N-myristoylation and found rules of the alphabet indexing. In addition, BONSAI suggested new requirements for the position of an amino acid in N-myristoylation signal.


Amino Acid Residue Amino Acid Requirement Amino Acid Pattern Acid Indexing Amino Alphabet Indexing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ryo Okada
    • 1
  • Manabu Sugii
    • 2
  • Hiroshi Matsuno
    • 1
  • Satoru Miyano
    • 3
  1. 1.Graduate School of Science and Engineering 
  2. 2.Media and Information Technology CenterYamaguchi UniversityYamaguchiJapan
  3. 3.Human Genome CenterUniversity of TokyoTokyoJapan

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