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  • Clustering of protein sequences is one of the techniques that can be helpful for predicting secondary structure of protein. Clustering methods are based on expressing similarity or dissimilarity of such sequences. The similarity of two protein sequences can be assessed by the score of the best alignment of the sequences. The paper deals with using formal model theory in describing this important task of bioinformatics. First, a well-known Needleman and Wunsch algorithm for finding the best alignment is introduced. Then a finite automaton that can compute the score for the best alignment is proposed.
  • Clustering of protein sequences is one of the techniques that can be helpful for predicting secondary structure of protein. Clustering methods are based on expressing similarity or dissimilarity of such sequences. The similarity of two protein sequences can be assessed by the score of the best alignment of the sequences. The paper deals with using formal model theory in describing this important task of bioinformatics. First, a well-known Needleman and Wunsch algorithm for finding the best alignment is introduced. Then a finite automaton that can compute the score for the best alignment is proposed. (en)
Title
  • Clustering of Protein Sequences
  • Clustering of Protein Sequences (en)
skos:prefLabel
  • Clustering of Protein Sequences
  • Clustering of Protein Sequences (en)
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  • RIV/00216305:26230/06:PU86203!RIV12-GA0-26230___
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  • P(GA102/05/0723)
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  • 468923
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  • RIV/00216305:26230/06:PU86203
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  • protein sequence, optimal alignment of two protein sequences, finite automaton, clustering, similarity function (en)
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  • [0A55BF03A103]
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  • Přerov
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  • Proceedings of 1st International Workshop WFM'06
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  • Burgetová, Ivana
  • Zendulka, Jaroslav
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number of pages
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  • Neuveden
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  • 80-86840-20-4
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  • 26230
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