Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJDMB.2011.045413
Title: Analysis of the relationships among Longest Common Subsequences, Shortest Common Supersequences and patterns and its application on pattern discovery in biological sequences
Authors: Ning, K.
Ng, H.K.
Leong, H.W. 
Keywords: Approximation algorithms
LCSs
Longest common subsequences
Pattern
Relationship
SCSs
Shortest common supersequences
Issue Date: 2011
Source: Ning, K.,Ng, H.K.,Leong, H.W. (2011). Analysis of the relationships among Longest Common Subsequences, Shortest Common Supersequences and patterns and its application on pattern discovery in biological sequences. International Journal of Data Mining and Bioinformatics 5 (6) : 611-625. ScholarBank@NUS Repository. https://doi.org/10.1504/IJDMB.2011.045413
Abstract: For a set of multiple sequences, their patterns, Longest Common Subsequences (LCS) and Shortest Common Supersequences (SCS) represent different aspects of these sequences- profile. Revealing the relationship between the patterns and LCS/SCS might provide us with a deeper view of the patterns. In this paper, we have showed that patterns LCS and SCS were closely related to each other. Based on their relations, the PALS algorithms are proposed to discover patterns in a set of biological sequences based on LCS and SCS results. Experiments show that the PALS algorithms are superior in efficiency and accuracy on a variety of sequences. Copyright © 2011 Inderscience Enterprises Ltd.
Source Title: International Journal of Data Mining and Bioinformatics
URI: http://scholarbank.nus.edu.sg/handle/10635/39605
ISSN: 17485673
DOI: 10.1504/IJDMB.2011.045413
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