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The Ruzzo–Tompa algorithm has been used in [[Bioinformatics]] tools to study biological data. The problem of finding disjoint maximal subsequences is of practical importance in the analysis of [[DNA]]. Maximal subsequences algorithms have been used in the identification of transmembrane segments and the evaluation of [[sequence homology]].<ref name="karlin">{{cite journal|last1=Karlin|first1=S|last2=Altschul|first2=SF|title=Applications and statistics for multiple high-scoring segments in molecular sequences|journal=Proceedings of the National Academy of Sciences of the United States of America|date=Jun 15, 1993|volume=90|issue=12|pages=5873–5877|pmid=8390686|pmc=46825|doi=10.1073/pnas.90.12.5873|bibcode=1993PNAS...90.5873K|doi-access=free}}</ref>
The algorithm is used in [[sequence alignment]] which is used as a method of identifying similar [[DNA]], [[RNA]], or [[protein]] sequences.<ref>{{Cite
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==Problem definition==
The problem of finding all maximal subsequences is defined as follows: Given a list of real numbered scores <math>x_1,x_2,\ldots,x_n</math>, find the list of contiguous subsequences that gives the greatest total score, where the score of each subsequence <math>S_{i,j} = \sum_{i\leq k\leq j} x_k</math>. The subsequences must be disjoint (non-overlapping) and have a positive score.<ref>{{Cite
==Other algorithms==
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