Parametric sequence comparisons.
Current algorithms can find optimal alignments of two nucleic acid or protein sequences, often by using dynamic programming. While the choice of algorithm penalty parameters greatly influences the quality of the resulting alignments, this choice has been done in an ad hoc manner. In this work, we present an algorithm to efficiently find the optimal alignments for all choices of the penalty parameters. It is then possible to systematically explore these alignments for those with the most biological or statistical interest. Several examples illustrate the method.
Waterman
M S
MS
Department of Mathematics, University of Southern California, Los Angeles 90089-1113.
Eggert
M
M
Lander
E
E
D000465:Algorithms; D000595:Amino Acid Sequence; D001483:Base Sequence; D008962:Models, Theoretical; D016415:Sequence Alignment; D012689:Sequence Homology, Nucleic Acid