Influence of Parameters in Multiple Sequence Alignment Methods for Protein Sequences

  • P. Manikandan
  • D. Ramyachitra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)


Protein sequence alignment is necessary to specify functions to unknown proteins. The alignment of protein sequences is used to determine the relatedness of organisms. Constructing a perfect multiple sequence alignment (MSA) for protein/DNA sequences without having similarity is a difficult task in computational biology. Nucleotide and amino acid sequence are ordered with feasible alignment, and minimal quantity of gap values is treated by multiple sequence alignment that expresses to the evolutionary, structural, and functional relationships between the protein/DNA sequences. This research work compares the various multiple sequence alignments such as Artificial Bee Colony (ABC), Bacterial Foraging Optimization (BFO), and online MSA tools, namely T-Coffee, Clustal Omega, and Muscle to predict the best method for aligning the sequences. The parameters such as single and double shift for ABC algorithm and swim length for BFO algorithm have been analyzed using 19% gap penalty values. The experiments were examined on different protein sequences, and the final result proves that the BFO algorithm obtains better significant results as compared with the other methods.


Multiple sequence alignment Artificial bee colony Bacterial foraging optimization T-Coffee Clustal Omega Muscle 



The authors are thankful to the DST, New Delhi, India (Grant Number: DST/INSPIRE Fellowship/2015/IF150093) for the financial grant under INSPIRE Fellowship scheme for this work.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceBharathiar UniversityCoimbatoreIndia

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