Prediction of Protein Beta-Sheets: Dynamic Programming versus Grammatical Approach
- 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
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.
Keywordsβ-sheet dynamic programming formal grammar computational complexity
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