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.