IEEE Access, Volume (8), No (1), Year (2020-1) , Pages (23838-23846)

Title : ( Simple and Efficient Pattern Matching Algorithms for Biological Sequences )

Authors: Peyman Neamatollahi , Muntasser Qrmshahe , Mahmoud Naghibzadeh ,

Citation: BibTeX | EndNote


The remarkable growth of biological data is a motivation to accelerate the discovery of solutions in many domains of computational bioinformatics. In different phases of the computational pipelines, pattern matching is a very practical operation. For example, pattern matching enables users to find the locations of particular DNA subsequences in a database or DNA sequence. Furthermore, in these expanding biological databases, some patterns are updated over time. To perform faster searches, high-speed pattern matching algorithms are needed. The present paper introduces three pattern matching algorithms that are specially formulated to speed up searches on large DNA sequences. The proposed algorithms raise performance by utilizing word processing (in place of the character processing presented in previous works) and also by searching the least frequent word of the pattern in the sequence. In terms of time cost, the experimental results demonstrate the superiority of the presented algorithms over the other simulated algorithms.


, Bioinformatics, string matching, DNA sequence, frequent pattern, exact algorithm
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

author = {Neamatollahi, Peyman and Qrmshahe, Muntasser and Naghibzadeh, Mahmoud},
title = {Simple and Efficient Pattern Matching Algorithms for Biological Sequences},
journal = {IEEE Access},
year = {2020},
volume = {8},
number = {1},
month = {January},
issn = {2169-3536},
pages = {23838--23846},
numpages = {8},
keywords = {Bioinformatics; string matching; DNA sequence; frequent pattern; exact algorithm},


%0 Journal Article
%T Simple and Efficient Pattern Matching Algorithms for Biological Sequences
%A Neamatollahi, Peyman
%A Qrmshahe, Muntasser
%A Naghibzadeh, Mahmoud
%J IEEE Access
%@ 2169-3536
%D 2020