An Improved Longest Common Subsequence Algorithm for Reducing Memory Complexity in Global Alignment of DNA Sequences

Parvinnia, Elham; Taheri, Mohammad; Ziarati, Koorush

doi:10.1109/bmei.2008.212

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…These directional pointers are used in the traceback step to obtain optimally aligned sequences for given DNA sequences. Needleman-Wunsch (NW) and Longest Common Subsequence (LCS) are the widely used methods for sequence alignment [23]. Both of these methods work on the concept of dynamic programming.…”

Section: Global Sequence Alignment Methodsmentioning

confidence: 99%

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Performance Analysis of Parallel Implementations of Global Sequence Alignment Methods for DNA Sequencing

Yadav¹,

Ahmed²,

Khan³

2023

IJCDS

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Global sequence alignment is an essential process in bio-informatics for determining the degree of similarity between two DNA sequences. It is performed using the Dynamic Programming (DP) approach, in which the problem is broken down into smaller ones, and these sub-problems are solved individually. There are various dynamic programming-based approaches to performing global sequence alignments, e.g.,Needleman-Wunsch (NW), Longest Common Subsequences (LCS). It is computationally difficult and complex to perform a global sequence alignment operation when the given DNA sequences are very large because programs based on dynamic programming are generally written to run sequentially. On the other hand, A well-written parallelized code executes many times faster than its equivalent serial code. This paper first explains the NW and LCS methods. Then the parallelization of these methods for shared memory and distributed memory architecture using OpenMP and MPI parallel paradigms is discussed in detail and compares the sequential and parallelized version of the Needleman-Wunsch and longest common subsequences. The detailed experiments for sequential and parallelized implementation of both methods were carried out by varying the DNA sequence length and number of threads in the case of OpenMP-based parallelization and the number of processes in the case of MPI-based parallelization. The obtained experimental results helped to perform a comparative performance evaluation based on the execution time of the sequential and parallel implementation of the methods. The speedup analysis of results showed that the parallelized implementations are many times faster than the equivalent sequential implementation, and MPI-based parallel implementation is approximately three times faster than the OpenMP-based parallel implementation.

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Section: Global Sequence Alignment Methodsmentioning

confidence: 99%

“…The score matrix for both LCS and NW methods can be generated row-wise [30]. In the row-wise approach, the score of each element of the score matrix is computed one row at a time, as shown in Figure 8(a).…”

Section: Parallel Approachmentioning

confidence: 99%

Performance Analysis of Parallel Implementations of Global Sequence Alignment Methods for DNA Sequencing

Yadav¹,

Ahmed²,

Khan³

2023

IJCDS

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“…The time complexity of this algorithm is O (n (m-r)). Elham Parvinnia, M. Taheri, Koorush Ziarati [2] proposed an Improved Longest Common Subsequence Algorithm for Reducing Memory Complexity in Global Alignment of DNA Sequences in 2008. Sergey Sheetlin, Yonil Park, and John L. Spouge [3] in 2011 proposed an objective method for estimating asymptotic parameters, with an application to sequence alignment.…”

Section: Literature Surveymentioning

confidence: 99%

A New DNA sequencing alignment methodology using the Longest Common Subsequence technique

Chowdhury

Mishra

2020

American Journal of Applied Mathematics and Computing

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The goal of this paper is to perform DNA sequence alignment using the Longest Common Sub-sequence Algorithm to obtain the longest common subsequence from the two strings X and Y for matching DNA in molecular biology etc. This paper would seek to establish the differences between the 2 species DNA and thereby conclude on their genetic similarity. The paper will be implemented in terms of space and time using the optimized longest common subsequence algorithm. This paper acts as a bridge between computer science and genomics, exploring the interdisciplinary area of computational biology and helping us to consider the very fundamental concepts of life and our relationship with other species.

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Subcubic Algorithms for the Sequence Excluded LCS Problem

Deorowicz

Grabowski

2014

Advances in Intelligent Systems and Computing

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An Improved Longest Common Subsequence Algorithm for Reducing Memory Complexity in Global Alignment of DNA Sequences

Cited by 4 publications

References 9 publications

Performance Analysis of Parallel Implementations of Global Sequence Alignment Methods for DNA Sequencing

Performance Analysis of Parallel Implementations of Global Sequence Alignment Methods for DNA Sequencing

A New DNA sequencing alignment methodology using the Longest Common Subsequence technique

Subcubic Algorithms for the Sequence Excluded LCS Problem

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