Represents the PROJECTION algorithm of Buhler and Tompa.
The type of sequences to be analyzed.
The Rng specialization to use for random number generation.
The Projection algorithm is a heuristic algorithm that does not guarantee that the unknown motif will be found every time. We can increase the chance of success by performing a large number of independent trials to generate multiple guesses. In each trial, Projection makes a preselection of sets of length-l patterns called l-mers which are likely to be a collection of motif instances (filtering step) and refines them by some local searching techniques, e.g. EM algorithm, Gibbs Sampling etc (refinement step).
|Displays all found motif candidates. In the case of the Projection Motif Finder the function displays the consensus pattern of the found motif candidate. (MotifFinder)|
|Represents the main function which is used to start the search for noticeable motif patterns. (MotifFinder)|
|Gets the motif out of a MotifFinder. If pos is given, the pos-th motif is returned, otherwise the first motif is returned. (MotifFinder)|
|Gets number of motifs in the MotifFinder. (MotifFinder)|
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