Performance Evaluation of Sine-Cosine Optimization Versus Particle Swarm Optimization for Global Sequence Alignment Problem

  • Mohamed IssaEmail author
  • Aboul Ella Hassanien
  • Ibrahim Ziedan
Part of the Studies in Computational Intelligence book series (SCI, volume 801)


Pairwise global sequence alignment is a vital process for finding functional and evolutionary similarity between biological sequences. The main usage of it is searching biological databases for finding the origin of unknown sequence. The standard global alignment based on dynamic programming approach which produces the accurate alignment but with extensive execution time. In this chapter, Sine-Cosine optimization algorithm was used for accelerating pairwise global alignment with alignment score near one produced by dynamic programming alignment. The reason for using Sine-Cosine optimization is its excellent exploration of the search space. The developed technique was tested on human and mouse protein sequences and was compared with classical global sequence alignment and alignment using Particle Swarm Optimization method.


Bioinformatics Sequence alignment Pairwise global alignment Meta-heuristics and Sine-Cosine optimization 



The first author would like to thank Yasmina Fakhry for her collaboration for provide facilities for providing this work.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mohamed Issa
    • 1
    Email author
  • Aboul Ella Hassanien
    • 2
  • Ibrahim Ziedan
    • 1
  1. 1.Department of Computer and Systems Engineering, Faculty of EngineeringZagazig UniversityZagazigEgypt
  2. 2.Faculty of Computer and InformationCairo UniversityGizaEgypt

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