Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
