A FAST TECHNIQUE FOR DERIVING FREQUENT STRUCTURED PATTERNS FROM BIOLOGICAL DATA SETS

Giorgio Terracina ()
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Giorgio Terracina: Dipartimento di Matematica, Università della Calabria, Via P. Bucci 87036 Rende (CS), Italy

New Mathematics and Natural Computation (NMNC), 2005, vol. 01, issue 02, 305-327

Abstract: In the last years, the completion of the human genome sequencing showed a wide range of new challenging issues involving raw data analysis. In particular, the discovery of information implicitly encoded in biological sequences is assuming a prominent role in identifying genetic diseases and in deciphering biological mechanisms. This information is usually represented by patterns frequently occurring in the sequences. Because of biological observations, a specific class of patterns is becoming particularly interesting:frequent structured patterns. In this respect, it is biologically meaningful to look at both "exact" and "approximate" repetitions of pattens within the available sequences. This paper gives a contribution in this setting by providing algorithms which allow to discover frequent structured patterns, both in "exact" and "approximate" form, present in a collection of input biological sequences.

Keywords: Sequence analysis; pattern discovery; frequent structured patterns; motifs (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1142/S1793005705000111

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