The SeSiMCMC (Sequence Similarities by Markov Chain Monte Carlo) algorithm finds DNA motifs of unknown length and complicated structure, such as direct repeats or palindromes with variable spacers in the middle in a set of unaligned DNA sequences. It uses an improved motif length estimator and careful Bayesian analysis to consider site absence in a sequence.
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A Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length.
Favorov AV, Gelfand MS, Gerasimova AV, Ravcheev DA, Mironov AA, Makeev VJ.
Bioinformatics. 2005 May 15;21(10):2240-5. Epub 2005 Feb 22.