1988/10/01 by Humberto Carrillo, Humberto Carrillo-Calvet, David J. Lipman +1 · 4 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Algorithms and Data Compression #Genomics and Phylogenetic Studies #Machine Learning in Bioinformatics
paper · doi:10.1137/0148063
crossref issued 1988/10/01 · crossref published 1988/10/01 · crossref published-print 1988/10/01 · openalex publication_date 1988/10/01 · crossref created 2005/02/23 · crossref deposited 2017/01/29 · openalex created_date 2025/10/10 · crossref indexed 2026/08/03 · openalex updated_date 2026/08/03
The study and comparison of sequences of characters from a finite alphabet is relevant to various areas of science, notably molecular biology. The measurement of sequence similarity involves the consideration of the different possible sequence alignments in order to find an optimal one for which the “distance” between sequences is minimum. By associating a path in a lattice to each alignment, a geometric insight can be brought into the problem of finding an optimal alignment. This problem can then be solved by applying a dynamic programming algorithm. However, the computational effort grows rapidly with the number N of sequences to be compared (O(lN )), where l is the mean length of the sequences to be compared). It is proved here that knowledge of the measure of an arbitrarily chosen alignment can be used in combination with information from the pairwise alignments to considerably restrict the size of the region of the lattice in consideration. This reduction implies fewer computations and less memory space needed to carry out the dynamic programming optimization process. The observations also suggest new variants of the multiple alignment problem.