English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

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

MPS-Authors

Schulz,  Marcel H.
Max Planck Society;

/persons/resource/persons50496

Robinson,  Peter N.
Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Schulz, M. H., Bauer, S., & Robinson, P. N. (2008). The generalised k-Truncated Suffix Tree for time- and space-efficient searches in multiple DNA or protein sequences. International Journal of Bioinformatics Research and Applications: Ijbra, 4(1), 81-95. doi:10.1504/IJBRA.2008.017165.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-80B3-8
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.