Akademik Veri Yönetim Sistemi
Journal of the Faculty of Engineering and Architecture of Gazi University, cilt.41, sa.1, ss.479-494, 2026 (SCI-Expanded, Scopus, TRDizin)
Bioinformatics is a scientific discipline that utilizes mathematics, computing, and statistics to conceptualize biological data and understand the relationships among them. The increasing volume of biological data has made the sequence alignment problem more complex, rendering manual solutions impractical. As a result, automated computational systems have been developed. Sequence alignment is categorized into pairwise and multiple sequence alignment. This study focuses on solving the multiple sequence alignment problem using heuristic methods such as Genetic Algorithm (GA), Differential Evolution (DE), and Simulated Annealing (SA). The GA, DE, GASA, and DESA algorithms are proposed, and alignments were performed on DNA sequences using the Needleman-Wunsch algorithm. Experimental results show that the GA algorithm has the shortest runtime, while the DE and DESA algorithms take longer to complete. GA, DE, and DESA produced higher alignment scores compared to GASA. When compared to ClustalW, the proposed algorithms achieved higher alignment accuracy in four datasets (trnN-GUU_rps12, rrn4.5_rps12, rrn5_rps12, psbT_pbf1). ClustalW stands out as the fastest method in terms of runtime and has the lowest theoretical computational complexity. In terms of efficiency (alignment score/runtime), ClustalW generally provides the highest efficiency. However, the proposed algorithms offer advantages in accuracy-focused applications and are particularly preferable in scenarios requiring highly precise alignments