Represents the ePatternBranching algorithm of Davila and Rajasekaran.
The EPatternBranching algorithm is an extended version of the well-known PatternBranching algorithm which was developed by Price et al. It is a heuristic algorithm such as Projection and uses a pattern-based approach. The algorithm searches in the space of possible motifs. The basic concept of EPatternBranching remains the same as in the original PatternBranching algorithm Starting from each l-mer
x in the input sequences the algorithm iteratively searches
around the vicinities of x and finds the best neighbors by applying a specific function
called bestNeighbors. At the end of each step, it selects those patterns from the set
of best neighbors that fulfill a particular condition and that are therefore qualified
for being a motif instance.
|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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