Using sequence compression to speedup probabilistic profile matching.

Valerio Freschi; Alessandro Bogliolo

doi:10.1093/bioinformatics/bti323

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Using sequence compression to speedup probabilistic profile matching.

Valerio Freschi·Alessandro Bogliolo

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Abstract

MOTIVATION: Matching a biological sequence against a probabilistic pattern (or profile) is a common task in computational biology. A probabilistic profile, represented as a scoring matrix, is more suitable than a deterministic pattern to retain the peculiarities of a given segment of a family of biological sequences. Brute-force algorithms take O(NP) to match a sequence of N characters against a profile of length P << N. RESULTS: In this work, we exploit string compression techniques to speedup brute-force profile matching. We present two algorithms, based on run-length and LZ78 encodings, that reduce computational complexity by the compression factor of the encoding.

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Algorithms Data Compression Gene Expression Profiling Models, Chemical Models, Statistical Sequence Alignment Sequence Analysis Sequence Homology Comparative Study Evaluation Study Journal Article

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BibTeX RIS

Valerio Freschi, Alessandro Bogliolo. 2005-02-15. Using sequence compression to speedup probabilistic profile matching.. https://doi.org/10.1093/bioinformatics%2Fbti323

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