The design and analysis of parallel algorithms
The design and analysis of parallel algorithms
Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization
Machine Learning - Special issue on applications in molecular biology
Finding motifs using random projections
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
Combinatorial Approaches to Finding Subtle Signals in DNA Sequences
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
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In bioinformatics, motif finding is one of the most common problems. It is to locate recurring patterns in the sequence of nucleotides or amino acids. The main difficulty of the problem is that the patterns are not exact matches owing to biological mutations. It is NP-complete. Within the literature many solutions have been provided for this challenging problem. Nevertheless, they do not address certain subtleties. Among them, one is addressed by Hu (2003). In this paper, we propose a parallel combinatorial algorithm for subtle motif finding on a Shared Memory Multiprocessor model. We suggest a method of implementation for the same.