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Abstract: Given a sequence of real numbers ("scores"), we present a practical linear time algorithm to find those nonoverlapping, contiguous subsequences having greatest total scores. This improves on the best previously known algorithm, which requires quadratic time in the worst case. The problem arises in biological sequence analysis, where the high-scoring subsequences correspond to regions of unusual composition in a nucleic acid or protein sequence. For instance, Altschul, Karlin, and others ... (Update)
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...negative and there are lower and upper bounds on the size of a tile. The papers which most closely relate to our work are the references [20] and [28] The authors in [20] provide an O(n) time algorithm to find all maximal scoring subsequences of a sequence of length n. In...
.... a linear algorithm for finding the maximal substrings and superstrings of two given strings was suggested in the context of bioinformatics [38]. Embedding a variation of this algorithm in our system will possibly reduce the complexity of string matching. Our home grown tool,...
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BibTeX entry: (Update)
Walter L. Ruzzo and Martin Tompa. A linear time algorithm for finding all maximal scoring subsequences. In Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology, pages 234--241, Heidelberg, Germany, August 1999. AAAI Press. http://citeseer.ist.psu.edu/article/ruzzo99linear.html More
@inproceedings{ ruzzo99linear,
author = "W. L. Ruzzo and M. Tompa",
title = "A Linear Time Algorithm for Finding All Maximal Scoring Subsequences",
booktitle = "Seventh International Conference on Intelligent Systems for Molecular Biology",
address = "Heidelberg, Germany",
pages = "234--241",
year = "1999",
url = "citeseer.ist.psu.edu/article/ruzzo99linear.html" }
Citations (may not include all citations):240 Identification of common molecular subsequences - Smith, Waterman - 1981
78 Programming Pearls (context) - Bentley - 1986
62 Introduction to Algorithms: A Creative Approach (context) - Manber - 1989
60 A simple method for displaying the hydropathic character of .. (context) - Kyte, Doolittle - 1982
25 Applications and statistics for multiple high-scoring segmen.. (context) - Karlin, Altschul - 1993
16 A new algorithm for best subsequence alignments with applica.. - Waterman, Eggert - 1987
15 Proofs as programs (context) - Bates, Constable - 1985
13 Locally optimal subalignments using nonlinear similarity fun.. (context) - Altschul, Erickson
13 Pattern recognition in genetic sequences by mismatch density (context) - Sellers - 1984
10 Strong limit theorems of empirical functionals for large exc.. (context) - Dembo, Karlin - 1991
8 Statistical composition of high-scoring segments from molecu.. (context) - Karlin, Dembo et al. - 1990
5 Compositional biases of bacterial genomes and evolutionary i.. (context) - Karlin, Mrazek et al. - 1997
4 A nonlinear measure of subalignment similarity and its signi.. (context) - Altschul, Erickson
3 Chance and significance in protein and DNA sequence analysis (context) - Karlin, Brendel - 1992
1 Evaluating the statistical significance of multiple distinct.. (context) - Altschul - 1997
1 Statistical-methods and insights for protein and 7th Intl (context) - Karlin, Bucher et al. - 1991
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