Class Specialization
EPatternBranching
Represents the ePatternBranching algorithm of Davila and Rajasekaran.
Note: There are various known problems with the motif finding in SeqAn. We plan to fix this in an upcoming release.
MotifFinder
EPatternBranching
MotifFinder<TValue, EPatternBranching, TRng>
Include Headers
seqan/find_motif.h
Parameters
TValue
The type of sequences to be analyzed.
Types: AminoAcid, Dna
Remarks
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
Metafunctions
ValueType of the items in the container or behind an iterator. (MotifFinder)
Functions
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 - www.seqan.de
 

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