The generalised k-Truncated Suffix Tree for time-and space-efficient searches in multiple DNA or protein sequences

Authors:
Marcel H. Schulz;Sebastian Bauer;Peter N. Robinson
Affiliations:
Institute fur Medizinische Genetik, Charite Universitatsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany/ International Max Planck Research School for Computational Biology and Scient ...;Institute fur Medizinische Genetik, Charite Universitatsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.;Institute fur Medizinische Genetik, Charite Universitatsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2008

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Abstract

Efficient searching for specific subsequences in a set of longer sequences is an important component of many bioinformatics algorithms. Generalised suffix trees and suffix arrays allow searches for a pattern of length n in time proportional to n independent of the length of the sequences, and are thus attractive for a variety of applications. Here, we present an algorithm termed the generalised k-Truncated Suffix Tree (kTST), that represents an adaption of Ukkonen's linear-time suffix tree construction algorithm. The kTST algorithm creates a k-deep tree in linear time that allows rapid searches for short patterns of length of up to k characters. The kTST can offer advantages in computational time and memory usage for searches for short sequences in DNA or protein sequences compared to other suffix-based algorithms.