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• W2032845906 abstract "Local alignment-free sequence comparison arises in the context of identifying similar segments of sequences that may not be alignable in the traditional sense. We propose a randomized approximation algorithm that is both accurate and efficient. We show that under D2 and its important variant as the similarity measure, local alignment-free comparison between a pair of sequences can be formulated as the problem of finding the maximum bichromatic dot product between two sets of points in high dimensions. We introduce a geometric framework that reduces this problem to that of finding the bichromatic closest pair (BCP), allowing the properties of the underlying metric to be leveraged. Local alignment-free sequence comparison can be solved by making a quadratic number of alignment-free substring comparisons. We show both theoretically and through empirical results on simulated data that our approximation algorithm requires a subquadratic number of such comparisons and trades only a small amount of accuracy to achieve this efficiency. Therefore, our algorithm can extend the current usage of alignment-free–based methods and can also be regarded as a substitute for local alignment algorithms in many biological studies." @default.
• W2032845906 created "2016-06-24" @default.
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• W2032845906 date "2013-07-01" @default.
• W2032845906 modified "2023-10-16" @default.
• W2032845906 title "A Geometric Interpretation for Local Alignment-Free Sequence Comparison" @default.
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• W2032845906 doi "https://doi.org/10.1089/cmb.2012.0280" @default.
• W2032845906 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3704055" @default.
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