Class Specialization
Represents the ePatternBranching algorithm of Davila and Rajasekaran.
MotifFinder<TValue, EPatternBranching, TRng>
Include Headers
The type of sequences to be analyzed.
Types: AminoAcid, Dna
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.
Specialization of
ValueType of the items in the container or behind an iterator. (MotifFinder)
displayResultDisplays all found motif candidates. In the case of the Projection Motif Finder the function displays the consensus pattern of the found motif candidate. (MotifFinder)
findMotifRepresents the main function which is used to start the search for noticeable motif patterns. (MotifFinder)
getMotifGets the motif out of a MotifFinder. If pos is given, the pos-th motif is returned, otherwise the first motif is returned. (MotifFinder)
motifCountGets number of motifs in the MotifFinder. (MotifFinder)
Example Programs
SeqAn - Sequence Analysis Library -

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