Class Specialization
EPatternBranching
Represents the ePatternBranching algorithm of Davila and Rajasekaran.
EPatternBranching |
Specialization of
Metafunctions
Type of the items in the container. (MotifFinder) |
Functions
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) |
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.
Example Programs
SeqAn - Sequence Analysis Library - www.seqan.de