The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
DNA Fragment Assembly Using Quantum-Inspired Genetic Algorithm
|
Author(s): Manisha Rathee (Jawaharlal Nehru University, India), Kumar Dilip (Jawaharlal Nehru University, India)and Ritu Rathee (Indira Gandhi Delhi Technical University for Women, India)
Copyright: 2019
Pages: 19
Source title:
Exploring Critical Approaches of Evolutionary Computation
Source Author(s)/Editor(s): Muhammad Sarfraz (Kuwait University, Kuwait)
DOI: 10.4018/978-1-5225-5832-3.ch005
Purchase
|
Abstract
DNA fragment assembly (DFA) is one of the most important and challenging problems in computational biology. DFA problem involves reconstruction of target DNA from several hundred (or thousands) of sequenced fragments by identifying the proper orientation and order of fragments. DFA problem is proved to be a NP-Hard combinatorial optimization problem. Metaheuristic techniques have the capability to handle large search spaces and therefore are well suited to deal with such problems. In this chapter, quantum-inspired genetic algorithm-based DNA fragment assembly (QGFA) approach has been proposed to perform the de novo assembly of DNA fragments using overlap-layout-consensus approach. To assess the efficacy of QGFA, it has been compared genetic algorithm, particle swarm optimization, and ant colony optimization-based metaheuristic approaches for solving DFA problem. Experimental results show that QGFA performs comparatively better (in terms of overlap score obtained and number of contigs produced) than other approaches considered herein.
Related Content
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
Stavros Kaperonis.
© 2024.
25 pages.
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
Nuno Geada.
© 2024.
12 pages.
|
|
|