Abstract
A scoring scheme is presented to measure the similarity score between two biological sequences, where matches are weighted dependent on their context The scheme generalizes a widely used scoring scheme. A dynamic programming algorithm is developed to compute a largest-scoring alignment of two sequences of lengths m and n in O(mn) time and O(m+n) space. Also developed is an algorithm for computing a largest-scoring local alignment between two sequences in quadratic time and linear space. Both algorithms are implemented as portable C programs. An experiment is conducted to compare protein alingments produced by the new global alignment program with ones by an existing program.
Keywords
- Linear Space
- Dynamic Programming Algorithm
- Recursive Call
- Biological Sequence
- Optimal Alignment
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This research was supported in part by NSF Grant DIR-9106510.
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© 1994 Springer-Verlag Berlin Heidelberg
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Huang, X. (1994). A context dependent method for comparing sequences. In: Crochemore, M., Gusfield, D. (eds) Combinatorial Pattern Matching. CPM 1994. Lecture Notes in Computer Science, vol 807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58094-8_5
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DOI: https://doi.org/10.1007/3-540-58094-8_5
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