Efficient algorithms for the longest common subsequence in $k$length substrings
Abstract
Finding the longest common subsequence in $k$length substrings (LCS$k$) is a recently proposed problem motivated by computational biology. This is a generalization of the wellknown LCS problem in which matching symbols from two sequences $A$ and $B$ are replaced with matching nonoverlapping substrings of length $k$ from $A$ and $B$. We propose several algorithms for LCS$k$, being nontrivial incarnations of the major concepts known from LCS research (dynamic programming, sparse dynamic programming, tabulation). Our algorithms make use of a lineartime and linearspace preprocessing finding the occurrences of all the substrings of length $k$ from one sequence in the other sequence.
 Publication:

arXiv eprints
 Pub Date:
 November 2013
 arXiv:
 arXiv:1311.4552
 Bibcode:
 2013arXiv1311.4552D
 Keywords:

 Computer Science  Data Structures and Algorithms;
 68W32;
 F.2.2
 EPrint:
 Submitted to a journal