High-level analysis like PeakPicking, Quantitation, Identification, MapAlginment.
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| | SignalProcessing |
| | Signal processing classes (noise estimation, noise filters, basline filters)
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| | PeakPicking |
| | Classes for the transformation of raw ms data into peak data.
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| | FeatureFinder |
| | The feature detection algorithms.
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| | MapAlignment |
| | The map alignment algorithms.
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| | FeatureGrouping |
| | The feature grouping.
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| | Identification |
| | Protein and peptide identitfication classes.
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| | Clustering |
| | This class contains SpectraClustering classes These classes are components for clustering all kinds of data for which a distance relation, normalizable in the range of [0,1], is available. Mainly this will be data for which there is a corresponding CompareFunctor given (e.g. PeakSpectrum) that is yielding the similarity normalized in the range of [0,1] of such two elements, so it can easily converted to the needed distances.
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High-level analysis like PeakPicking, Quantitation, Identification, MapAlginment.