Using progressive methods for global multiple sequence alignment.
Finding a global optimal alignment of more than two sequences that includes matches, mismatches, and gaps and that takes into account the degree of variation in all of the sequences at the same time is especially difficult. The dynamic programming algorithm used for optimal alignment of pairs of sequences can be extended to global alignment of three sequences, but for more than three sequences, only a small number of relatively short sequences may be analyzed. Thus, approximate methods are used for global sequence alignment. One class of these methods is progressive global alignment, which starts with an alignment of the most alike sequences and then builds an alignment by adding more sequences. This article introduces three programs that use progressive alignment methodology.
Mount
David W
DW
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D005914:Globins / Q000737:chemistry*; D006801:Humans; D008969:Molecular Sequence Data; D010802:Phylogeny; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software
D005914:Globins