MotifSampler tries to find over-represented motifs in the upstream region of a set of co-regulated genes. This motif finding algorithm uses Gibbs sampling to find the position probability matrix that represents the motif. In this implementation we focus on the use of higher-order background models to improve the robustness of the motif finding. At the moment the MotifSampler comes with background models for several organisms (see pop up list further down the page).
This web interface is merely intended to hint at the capabilities of MotifSampler. MotifSampler is a stochastic method and can/will give different results when run with the same parameters several times. This might seem as a disadvantage but it becomes a real advantage when using the tool in a constructive manner (doing multiple runs and post-processing the results). To do this type of analysis you should not use the website, but you rather use the stand-alone version. Please also check the help pages for more information.
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