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EnglishIn this paper we introduce a new alignment-free method for comparing sequences which is combinatorial by nature and does not use any compressor nor any information-theoretic notion. Such a method is based on an extension of the Burrows-Wheeler Transform, a transformation widely used in the context of Data Compression. The new extended transformation takes as input a multiset of sequences and produces as output a string obtained by a suitable rearrangement of the characters of all the input sequences. By using such a transformation we give a general method for comparing sequences that takes into account how much the characters coming from the different input sequences are mixed in the output string. Such a method is tested on a real data set for the whole mitochondrial genome phylogeny problem. However, the goal of this paper is to introduce a new and general methodology for automatic categorization of sequences.
Mantaci, S., Restivo, A., Rosone, G., & Sciortino, M. (2008). A New Combinatorial Approach to Sequence Comparison. THEORY OF COMPUTING SYSTEMS, 42(3), 411-429 [10.1007/s00224-007-9078-6].
| Data di pubblicazione: | 2008 | |
| Titolo: | A New Combinatorial Approach to Sequence Comparison | |
| Autori: | ||
| Citazione: | Mantaci, S., Restivo, A., Rosone, G., & Sciortino, M. (2008). A New Combinatorial Approach to Sequence Comparison. THEORY OF COMPUTING SYSTEMS, 42(3), 411-429 [10.1007/s00224-007-9078-6]. | |
| Rivista: | ||
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/s00224-007-9078-6 | |
| Abstract: | In this paper we introduce a new alignment-free method for comparing sequences which is combinatorial by nature and does not use any compressor nor any information-theoretic notion. Such a method is based on an extension of the Burrows-Wheeler Transform, a transformation widely used in the context of Data Compression. The new extended transformation takes as input a multiset of sequences and produces as output a string obtained by a suitable rearrangement of the characters of all the input sequences. By using such a transformation we give a general method for comparing sequences that takes into account how much the characters coming from the different input sequences are mixed in the output string. Such a method is tested on a real data set for the whole mitochondrial genome phylogeny problem. However, the goal of this paper is to introduce a new and general methodology for automatic categorization of sequences. | |
| Appare nelle tipologie: | 1.01 Articolo in rivista |
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http://hdl.handle.net/10447/13319
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