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## Uses of Interface
de.jstacs.motifDiscovery.MotifDiscoverer

Packages that use MotifDiscoverer
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer
de.jstacs.sequenceScores.statisticalModels.differentiable | Provides all `DifferentiableStatisticalModel`s, which can compute the gradient with respect to their parameters for a given input `Sequence`.
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture | Provides `DifferentiableSequenceScore`s that are mixtures of other `DifferentiableSequenceScore`s.
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif |
de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif |

Uses of MotifDiscoverer in de.jstacs.motifDiscovery

Subinterfaces of MotifDiscoverer in de.jstacs.motifDiscovery
`interface` | `MutableMotifDiscoverer` This is the interface that any tool for de-novo motif discovery should implement that allows any modify-operations like shift, shrink and expand.

Methods in de.jstacs.motifDiscovery that return MotifDiscoverer
`MotifDiscoverer` | `MotifDiscoverer.clone()` This method returns a deep clone of the instance.
`MotifDiscoverer` | `SignificantMotifOccurrencesFinder.getMotifDiscoverer()` This method returns a clone of the internally used `MotifDiscoverer`.

Methods in de.jstacs.motifDiscovery with parameters of type MotifDiscoverer
`static ImageResult` | `MotifDiscovererToolBox.plot(MotifDiscoverer motifDisc, int component, int motif, Sequence sequence, int startpos, REnvironment r, int width, int height, MotifDiscoverer.KindOfProfile kind)` This method creates a simple plot of the profile of scores for a sequence and a start position.
`static ImageResult` | `MotifDiscovererToolBox.plotAndAnnotate(MotifDiscoverer motifDisc, int component, int motif, Sequence sequence, int startpos, REnvironment r, int width, int height, double yMin, double yMax, double threshold, MotifDiscoverer.KindOfProfile kind)` This method creates a plot of the profile of scores for a sequence and a start position and annotates bindings sites in the plot that have a higher score than `threshold`.

Constructors in de.jstacs.motifDiscovery with parameters of type MotifDiscoverer
`SignificantMotifOccurrencesFinder(MotifDiscoverer disc, DataSet bg, double[] weights, double sign)` This constructor creates an instance of `SignificantMotifOccurrencesFinder` that uses a `DataSet` to determine the siginificance level.
`SignificantMotifOccurrencesFinder(MotifDiscoverer disc, SignificantMotifOccurrencesFinder.JoinMethod joiner, DataSet bg, double[] weights, double sign)` This constructor creates an instance of `SignificantMotifOccurrencesFinder` that uses a `DataSet` to determine the siginificance level.
`SignificantMotifOccurrencesFinder(MotifDiscoverer disc, SignificantMotifOccurrencesFinder.RandomSeqType type, boolean oneHistogram, int numSequences, double sign)` This constructor creates an instance of `SignificantMotifOccurrencesFinder` that uses the given `SignificantMotifOccurrencesFinder.RandomSeqType` to determine the siginificance level.
`SignificantMotifOccurrencesFinder(MotifDiscoverer disc, SignificantMotifOccurrencesFinder.RandomSeqType type, SignificantMotifOccurrencesFinder.JoinMethod joiner, boolean oneHistogram, int numSequences, double sign)` This constructor creates an instance of `SignificantMotifOccurrencesFinder` that uses the given `SignificantMotifOccurrencesFinder.RandomSeqType` to determine the siginificance level.

Uses of MotifDiscoverer in de.jstacs.sequenceScores.statisticalModels.differentiable

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable that implement MotifDiscoverer
`class` | `IndependentProductDiffSM` This class enables the user to model parts of a sequence independent of each other.
`class` | `MappingDiffSM` This class implements a `DifferentiableStatisticalModel` that works on mapped `Sequence`s.

Uses of MotifDiscoverer in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture that implement MotifDiscoverer
`class` | `MixtureDiffSM` This class implements a real mixture model.
`class` | `VariableLengthMixtureDiffSM` This class implements a mixture of `VariableLengthDiffSM` by extending `MixtureDiffSM` and implementing the methods of `VariableLengthDiffSM`.

Uses of MotifDiscoverer in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif that implement MotifDiscoverer
`class` | `ExtendedZOOPSDiffSM` This class handles mixtures with at least one hidden motif.

Uses of MotifDiscoverer in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif that implement MotifDiscoverer
`class` | `HiddenMotifMixture` This is the main class that every generative motif discoverer should implement.
`class` | `ZOOPSTrainSM` This class enables the user to search for a single motif in a sequence.

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