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Titlebook: Combinatorial Pattern Matching; 12th Annual Symposiu Gad M. Landau,Amihood Amir Conference proceedings 2001 Springer-Verlag Berlin Heidelbe

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Xin-tong Pei,Jian-jun Zeng,Zhen-jang Zhangf . tandem copies), and the alignment must include all of . and all of .. Our algorithm allows any alignment scoring scheme with . gap costs and runs in time .. We have used it to identify related tandem repeats in the .. . genome as part of the development of a multi-genome database of tandem repeats.
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Zhaonian Li,Changxiang Chen,ZhenJiang Zhang by Uno and Yagiura (. 26, 290-309, 2000) who present an algorithm to find all . common intervals of . = 2 permutations in optimal . time and . space. To achieve our result, we introduce the set of ., a generating subset of the set of all common intervals of . permutations.
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A Very Elementary Presentation of the Hannenhalli-Pevzner Theory, and manipulation of various graphs..Here we give the first completely elementary treatment of this problem. We characterize . and . working directly on the origi- nal signed permutation. Moreover, our presentation leads to polynomial algorithms that can be efficiently implemented using bit-wise operations.
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Lu Xu,Li Jianwei,Jiang Hao,Luo Dan,Cao Han the first nontrivial result for this problem. The experimental results show that our compressed search algorithm needs half the time necessary for decompression plus searching, which is currently the only alternative.
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https://doi.org/10.1007/978-3-030-73562-3n of . letters (m0 runs) in a text of . letters (. runs) in . time, both for LCS and Levenshtein models. Then we propose improvements for a greedy algorithm for the LCS, and conjecture that the improved algorithm has . expected case complexity. Experimental results are provided to support the conjecture.
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https://doi.org/10.1007/978-3-031-31733-0by, but not exactly matched, can still be considered to be almost identical. We here define a “fuzzy Hamming distance” that extends the Hamming concept to give partial credit for near misses, and suggest a dynamic programming algorithm that permits it to be computed efficiently. We envision many uses for such a measure.
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https://doi.org/10.1007/978-3-030-73562-3really simple to implement. We also extend the . to predict that a string could be a suffix (.. in the set ..::: ..) of .. We obtain the ., that enables in some cases a tricky improvement of the previous string matching algorithm.
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