Patterns in biological sequences are important for revealing the relationship among biological sequences. Much research has been done on this problem, and the sensitivity and specificity of current algorithms are already quite satisfactory. However, in general, for problems on a set of sequences, the relationship among their patterns, their Longest Common Subsequences (LCS) and their Shortest Common Supersequences (SCS) are not examined carefully. Therefore, revealing the relationship between the patterns and LCS/SCS might provide us with a deeper view of the patterns of biological sequences, in turn leading to a better understanding of them. In this paper, we propose the PALS (PAtterns by Lcs and Scs) algorithms to discover patterns in a set of biological sequences by first generating the results for LCS and SCS of sequences by heuristic, and consequently derive the patterns from these results. Experiments show that the PALS algorithms perform well (both in efficiencies and in accuracies) on a variety of sequences.
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