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Abstract: Sequence alignment in genomics and proteomics is mostly done via dynamic programming (DP) based approaches. In this work, we show how computational results from DP can be reused to update alignments when analyzing new versions of a sequence. We derive relative tolerance bounds on node distances from a root node that guarantee that partial shortest path distances remain optimal. We then propose an algorithm that uses these bounds to skip all unperturbed parts of a sequence when recomputing an... (Update)
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BibTeX entry: (Update)
@misc{ and-reusable,
author = "Changjin Hong And",
title = "Reusable Dynamic Programming:updating Sequence Alignment",
url = "citeseer.ist.psu.edu/765228.html" }
Citations (may not include all citations):3972 Introduction to Algorithms (context) - Cormen, Leiserson et al. - 1992
431 A Basic Local Alignment Search Tool (context) - Altschul, Gish et al. - 1990
57 Algorithms for the Longest Common Subsequence Problem (context) - Hirschberg - 1977
5 Arc Tolerances in Shortest Path and Network Flow Problems (context) - Shier - 1980
1 Finding the K Smallest Spanning Trees - Eppstein - 1990
1 Handling Updates of A Biological Sequence Based on Hidden Ma.. (context) - Hong, Tewfik et al. - 2005
http://www.ncbi.nlm.nih.gov/
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