Ruzzo–Tompa algorithm

The Ruzzo–Tompa algorithm is a linear-time algorithm for finding all non-overlapping, contiguous, maximal scoring subsequences in a sequence of real numbers. This algorithm is an improvement over previously known quadratic time algorithms. The maximum scoring subsequence from the set produced by the algorithm is also a solution to the maximum subarray problem. The Ruzzo–Tompa algorithm has applications in bioinformatics, web scraping, and information retrieval.

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enThe Ruzzo–Tompa algorithm is a linear-time algorithm for finding all non-overlapping, contiguous, maximal scoring subsequences in a sequence of real numbers. This algorithm is an improvement over previously known quadratic time algorithms. The maximum scoring subsequence from the set produced by the algorithm is also a solution to the maximum subarray problem. The Ruzzo–Tompa algorithm has applications in bioinformatics, web scraping, and information retrieval.
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enThe Ruzzo–Tompa algorithm is a linear-time algorithm for finding all non-overlapping, contiguous, maximal scoring subsequences in a sequence of real numbers. This algorithm is an improvement over previously known quadratic time algorithms. The maximum scoring subsequence from the set produced by the algorithm is also a solution to the maximum subarray problem. The Ruzzo–Tompa algorithm has applications in bioinformatics, web scraping, and information retrieval.
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Ruzzo–Tompa algorithm
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enRuzzo–Tompa algorithm
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Algorithm
Bioinformatics
Bursting
Category:Articles with example Python (programming language) code
Category:Dynamic programming
Category:Optimization algorithms and methods
Data fusion
DNA
Dynamic programming
File:Animation of Ruzzo-Tompa Algorithm.ogv
Information retrieval
Lexical analysis
Maximum subarray problem
Protein
Python (programming language)
Quicksort
RNA
Sequence alignment
Sequence homology
Time complexity
Web scraping
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Q55632140
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Category:Articles with example Python (programming language) code
Category:Dynamic programming
Category:Optimization algorithms and methods
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