Transformation Distances, Strings and Identification of DNA Promoters.
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by Maciej Marczak, Włodzisław Duch, Karol Grudziński, Antoine Naud
http://www.phys.uni.torun.pl/publications/kmk/02-TS-promoters.pdf
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Abstract:
Abstract. Computational intelligence methods usually work in vector spaces and are not able to deal with objects that have complex structures. Methods based on similarity may be applied in structural domains. Similarity may be defined by minimal cost needed to transform one object into another. The costs of the substitution operations that such transformation is composed from may be treated as adaptive parameters. For strings this leads to a generalization of edit (Levenshtein) distance. This distance is computed using dynamic programming method and applied to the problem of identifying DNA gene promoter sequences. 1
