Algorithms for extracting motifs from biological weighted sequences

Authors:
C. Iliopoulos;K. Perdikuri;E. Theodoridis;A. Tsakalidis;K. Tsichlas
Affiliations:
Department of Computer Science, King's College London, London WC2R 2LS, England, UK;Computer Engineering & Informatics Department of University of Patras, 26500 Patras, Greece and Research Academic Computer Technology Institute (RACTI), 61 Riga Feraiou Str., 26221 Patras, Greece;Computer Engineering & Informatics Department of University of Patras, 26500 Patras, Greece and Research Academic Computer Technology Institute (RACTI), 61 Riga Feraiou Str., 26221 Patras, Greece;Computer Engineering & Informatics Department of University of Patras, 26500 Patras, Greece and Research Academic Computer Technology Institute (RACTI), 61 Riga Feraiou Str., 26221 Patras, Greece;Department of Computer Science, King's College London, London WC2R 2LS, England, UK
Venue:
Journal of Discrete Algorithms
Year:
2007

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Abstract

In this paper we present three algorithms for the Motif Identification Problem in Biological Weighted Sequences. The first algorithm extracts repeated motifs from a biological weighted sequence. The motifs correspond to repetitive words which are approximately equal, under a Hamming distance, with probability of occurrence =1/k, where k is a small constant. The second algorithm extracts common motifs from a set of N=2 weighted sequences. In this case, the motifs consists of words that must occur with probability =1/k, in 1=