Article: Aligning molecular sequences using hybrid bioinspired algorithm in GPU Journal: International Journal of Computational Science and Engineering (IJCSE) 2020 Vol.21 No.1 pp.125 - 136 Abstract: To explicate the functionality of the basic cell, there is a need for the study of bioinformatics. To better understand the structural and functional information of molecules, sequence analysis is considered as the root domain. In this, aligning the sequence is the first step, an NP-complete problem like all biological problems. Owing to the increased molecular data in biology, there is a demand for the development of efficient approaches to this sequence alignment problem. From the study it is concluded that there is trade-off between accuracy and computational time. Focusing on the latter in this paper, a new parallel hybridised bio-inspired approach (PGWOGO) is proposed without sacrificing the accuracy. A grey wolf optimiser technique is hybridised with the genetic operators and the parallel phases are implemented in Quadro 4,000 graphics processing unit. A new crossover and mutation operator's namely horizontal crossover and local gaps shuffle mutation operator between aligned blocks are employed. The performance of proposed algorithm is evaluated using the cells update per second (CUPS) and compared with the state-of-the-art techniques. The results show that the proposed algorithm yields better alignment than other techniques. Inderscience Publishers - linking academia, business and industry through research

Title: Aligning molecular sequences using hybrid bioinspired algorithm in GPU

Authors: J. Jayapriya; Michael Arock

Addresses: Department of Computer Applications, National Institute of Technology, Tiruchirappalli, TamilNadu, India ' Department of Computer Applications, National Institute of Technology, Tiruchirappalli, TamilNadu, India

Abstract: To explicate the functionality of the basic cell, there is a need for the study of bioinformatics. To better understand the structural and functional information of molecules, sequence analysis is considered as the root domain. In this, aligning the sequence is the first step, an NP-complete problem like all biological problems. Owing to the increased molecular data in biology, there is a demand for the development of efficient approaches to this sequence alignment problem. From the study it is concluded that there is trade-off between accuracy and computational time. Focusing on the latter in this paper, a new parallel hybridised bio-inspired approach (PGWOGO) is proposed without sacrificing the accuracy. A grey wolf optimiser technique is hybridised with the genetic operators and the parallel phases are implemented in Quadro 4,000 graphics processing unit. A new crossover and mutation operator's namely horizontal crossover and local gaps shuffle mutation operator between aligned blocks are employed. The performance of proposed algorithm is evaluated using the cells update per second (CUPS) and compared with the state-of-the-art techniques. The results show that the proposed algorithm yields better alignment than other techniques.

Keywords: graphical processing unit; GPU; alignment; hybrid bioinspired; grey wolf optimiser; GWO; genetic operators; crossover; mutation.

DOI: 10.1504/IJCSE.2020.105219

International Journal of Computational Science and Engineering, 2020 Vol.21 No.1, pp.125 - 136

Received: 02 Feb 2017
Accepted: 16 Feb 2018
Published online: 22 Feb 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Aligning molecular sequences using hybrid bioinspired algorithm in GPU

Keep up-to-date