Abstract
Context: Pairwise sequence alignment is one of the ways to arrange two biological sequences to identify regions of resemblance that may suggest the functional, structural, and/or evolutionary relationship (proteins or nucleic acids) between the sequences. There are two strategies in pairwise sequence alignment: Local sequence Alignment (Smith-waterman algorithm) and Global sequence Alignment (Needleman-Wunsch algorithm). In local sequence alignment, two sequences that may or may not be related are aligned to find regions of local similarities in large sequences whereas in global sequence alignment, two sequences same in length are aligned to identify conserved regions. Similarities and divergence between biological sequences identified by sequence alignment also have to be rationalized and visualized in the sense of phylogenetic trees. The phylogenetic tree construction methods are divided into distance-based and character-based methods. Evidence Acquisition: In this article, different algorithms of sequence alignment and phylogenetic tree construction were studied with examples and compared to establish the best among them to look into background of these methods for the better understanding of computational phylogenetics.Conclusions: Pairwise sequence alignment is a very important part of bioinformatics to compare biological sequences to find similarities among them. The alignment data is visualized through phylogenetic tree diagram that shows evolutionary history among organisms. Phylogenetic tree is constructed through various methods some are easier but does not provide accurate evolutionary data whereas others provide accurate evolutionary distance among organism but are computationally exhaustive.
Adaptive memory programming: local search parallel algorithms for phylogenetic tree construction
