Prediction of Protein Beta-Sheets: Dynamic Programming versus Grammatical Approach

  • Yuki Kato
  • Tatsuya Akutsu
  • Hiroyuki Seki
Conference paper

DOI: 10.1007/978-3-540-88436-1_6

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5265)
Cite this paper as:
Kato Y., Akutsu T., Seki H. (2008) Prediction of Protein Beta-Sheets: Dynamic Programming versus Grammatical Approach. In: Chetty M., Ngom A., Ahmad S. (eds) Pattern Recognition in Bioinformatics. PRIB 2008. Lecture Notes in Computer Science, vol 5265. Springer, Berlin, Heidelberg

Abstract

Protein secondary structure prediction is one major task in bioinformatics and various methods in pattern recognition and machine learning have been applied. In particular, it is a challenge to predict β-sheet structures since they range over several discontinuous regions in an amino acid sequence. In this paper, we propose a dynamic programming algorithm for some kind of antiparallel β-sheet, where the proposed approach can be extended for more general classes of β-sheets. Experimental results for real data show that our prediction algorithm has good performance in accuracy. We also show a relation between the proposed algorithm and a grammar-based method. Furthermore, we prove that prediction of planar β-sheet structures is NP-hard.

Keywords

β-sheet dynamic programming formal grammar computational complexity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yuki Kato
    • 1
  • Tatsuya Akutsu
    • 1
  • Hiroyuki Seki
    • 2
  1. 1.Bioinformatics Center, Institute for Chemical ResearchKyoto UniversityGokasho, UjiJapan
  2. 2.Graduate School of Information ScienceNara Institute of Science and TechnologyIkomaJapan

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