Fast profile matching algorithms – A survey
Theoretical Computer Science
Fast search algorithms for position specific scoring matrices
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Finding Significant Matches of Position Weight Matrices in Linear Time
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Parallel Position Weight Matrices algorithms
Parallel Computing
A simple pattern matching algorithm for weighted sequences
Proceedings of the 2012 ACM Research in Applied Computation Symposium
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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. Contact: bogliolo@sti.uniurb.it