An Efficient Algorithm for LCS Problem between Two Arbitrary Sequences

Common Subsequence ◽

Science Problem ◽

Essential Problem

The longest common subsequence (LCS) problem is a classic computer science problem. For the essential problem of computing LCS between two arbitrary sequences s1 and s2, this paper proposes an algorithm taking O(n+r) space and O(r+n2) time, where r is the total number of elements in the set (i,j)|s1[i]=s2[j]. The algorithm can be more efficient than relevant classical algorithms in specific ranges of r.

A New Efficient Algorithm for Computing the Longest Common Subsequence

Theory of Computing Systems ◽

10.1007/s00224-008-9101-6 ◽

2008 ◽

Vol 45 (2) ◽

pp. 355-371 ◽

Cited By ~ 18

Author(s):

Costas S. Iliopoulos ◽

M. Sohel Rahman

Keyword(s):

Efficient Algorithm ◽

A Branch Elimination-based Efficient Algorithm for Large-scale Multiple Longest Common Subsequence Problem

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2021.3115057 ◽

2021 ◽

pp. 1-1

Author(s):

Shiwei Wei ◽

Yuping Wang ◽

Yiu-ming Cheung

Keyword(s):

Efficient Algorithm ◽

Large Scale ◽

Longest Common Subsequence Problem ◽

A space efficient algorithm for the longest common subsequence in k -length substrings

Theoretical Computer Science ◽

10.1016/j.tcs.2017.05.015 ◽

2017 ◽

Vol 687 ◽

pp. 79-92 ◽

Cited By ~ 1

Author(s):

Daxin Zhu ◽

Lei Wang ◽

Tinran Wang ◽

Xiaodong Wang

Keyword(s):

Efficient Algorithm ◽

A time efficient algorithm for finding longest common subsequence from two molecular sequences

2007 IEEE 33rd Annual Northeast Bioengineering Conference ◽

10.1109/nebc.2007.4413398 ◽

2007 ◽

Author(s):

S.A.M Rizvi ◽

Pankaj Agarwal

Keyword(s):

Efficient Algorithm ◽

Molecular Sequences ◽

An Efficient Technique for Finding Longest Common Subsequence of DNA Sequences

American Journal of Advanced Computing ◽

10.15864/ajac.1101 ◽

2020 ◽

Vol 1 (1) ◽

pp. 1-5

Author(s):

Tamal Chakrabarti ◽

Devadatta Sinha

Keyword(s):

Computer Science ◽

Human Genome ◽

Dna Sequences ◽

Base Pairs ◽

Effective Technique ◽

Dna Base ◽

Wide Range ◽

Dna Base Pairs ◽

Molecular biologists rely very heavily on computer science algorithms as research tools. The process of finding the longest common subsequence of two DNA sequences has a wide range of applications in modern bioinformatics. Genetics databases can hold enormous amounts of raw data, for example the human genome consists of approximately three billion DNA base pairs. The processing of this gigantic volume of data necessitates the use of extremely efficient string algorithms. This paper introduces a space and time effective technique for retrieving the longest common subsequence of DNA sequences.