its corresponding tree: Bioinformatics The distance matrix is widely used in the bioinformatics field, and it is present in several methods, algorithms and programs. Distance matrices are used to represent protein structures in a coordinate-independent manner, as well as the pairwise distances between two sequences in sequence space. They are used in structural and sequential alignment, and for the determination of protein structures from NMR or X-ray crystallography. Sometimes it is more convenient to express data as a similarity matrix. It is also used to define the distance correlation. Sequence alignment An alignment of two sequences is formed by inserting spaces in arbitrary locations along the sequences so that they end up with the same length and there are no two spaces at the same position of the two augmented sequences. One of the primary methods for sequence alignment is dynamic programming. The method is used to fill the distance matrix and then obtain the alignment. In typical usage, for sequence alignment a matrix is used to assign scores to amino-acid matches or mismatches, and a gap penalty for matching an amino-acid in one sequence with a gap in the other. Global alignment The Needleman-Wunsch algorithm used to calculate global alignment uses dynamic programming to obtain the distance matrix. Local alignment The Smith-Waterman algorithm is also dynamic programing based which consists also in obtaining the distance matrix and then obtain the local alignment. Multiple sequence alignment Multiple sequence alignment is an extension of pairwise alignment to align several sequences at a time. Different MSA methods are based on the same idea of the distance matrix as global and local alignments. Center star method. This method defines a center sequence which minimizes the distance between the sequence and any other sequence . Then it generates a multiple alignment for the set of sequences so that for every the alignment distance is the optimal pairwise alignment. This method has the characteristic that the computed alignment for whose sum-of-pair distance is at most twice the optimal multiple alignment. Progressive alignment method. This heuristic method to create MSA first aligns the two most related sequences, and the it progressively aligns the next two most related sequences until all sequences are aligned There are other methods that have their own program due to their popularity: ClustalW MUSCLE MAFFT MANGO And many more MAFFT Multiple alignment using fast fourier transform (MAFFT) is a program with an