Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Chimeric alignment by dynamic programming: algorithm and biological uses
RECOMB '97 Proceedings of the first annual international conference on Computational molecular biology
The Complexity of Some Problems on Subsequences and Supersequences
Journal of the ACM (JACM)
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
On the common substring alignment problem
Journal of Algorithms
Sparse LCS common substring alignment
Information Processing Letters
Efficient algorithms for finding interleaving relationship between sequences
Information Processing Letters
Efficient algorithms for the block edit problems
Information and Computation
Hi-index | 0.89 |
The longest common subsequence (LCS) problem can be used to measure the relationship between sequences. In general, the inputs of the LCS problem are two sequences. For finding the relationship between one sequence and a set of sequences, we cannot apply the traditional LCS algorithms immediately. In this paper, we define the mosaic LCS (MLCS) problem of finding a mosaic sequence C, composed of repeatable k sequences in source sequence set S, such that the LCS of C and the target sequence T is maximal. Based on the concept of break points in sequence T, we first propose a divide-and-conquer algorithm with O(n^2m|S|+n^3logk) time for solving this problem, where n and m are the length of T and the maximal length of sequences in S, respectively. Furthermore, an improved algorithm with O(n(m+k)|S|) time is proposed by applying an efficient preprocessing for the MLCS problem.