Current Trends and Ongoing Progress in the Computational Alignment of Biological Sequences

Abstract

The computational techniques for nucleic acid and protein sequence comparison reduce the extensive burden of molecular biologists. The sequence alignment is one of the main research areas in bioinformatics, and comparative genomics and proteomics lead us to important discoveries in various fields of bioinformatics. Researchers develop and use different heuristics and evolutionary algorithms for optimal DNA and protein sequence alignment. There are different categories of improved computational sequence matching methods. In this paper, the goal is to cover almost all computational approaches toward sequence alignment. Different aspects and issues related to the optimal alignment of biological sequences will be analyzed. The sequence comparisons through mathematical and computational techniques have manifold benefits and importance in bioinformatics. Researchers recently explore proposing novel computational techniques for simultaneous matching of multiple sequences or multiple sequence alignment (MSA). Pairwise alignment, or the alignment of two sequences, is the basic building block of all alignment methods. The goal is to design optimal and relevant algorithms with less computational complexity and more efficiency.

Keywords

• Dynamic programming optimization
• multiple sequence alignment
• evolutionary computations
• categories of sequence alignment
• recent trends in sequence alignment
• local and global alignment