
pmid: 7922677
We present a dynamic programming algorithm for computing a best global alignment of two sequences. The proposed algorithm is robust in identifying any of several global relationships between two sequences. The algorithm delivers a best alignment of two sequences in linear space and quadratic time. We also describe a multiple alignment algorithm based on the pairwise algorithm. Both algorithms have been implemented as portable C programs. Experimental results indicate that for a commonly used set of gap penalties, the new programs produce more satisfactory alignments on sequences of various lengths than some existing pairwise and multiple programs based on the dynamic programming algorithm of Needleman and Wunsch.
Molecular Sequence Data, Myosins, Globins, Species Specificity, Caenorhabditis, Animals, Humans, Dictyostelium, Drosophila, Programming Languages, Amino Acid Sequence, Rabbits, Chickens, Sequence Alignment, Algorithms, Software
Molecular Sequence Data, Myosins, Globins, Species Specificity, Caenorhabditis, Animals, Humans, Dictyostelium, Drosophila, Programming Languages, Amino Acid Sequence, Rabbits, Chickens, Sequence Alignment, Algorithms, Software
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