1. A classification system ( 100 ) for classifying biomolecular data, comprising an input for receiving measurement data comprising measurements of a plurality of numerical features ( 102 ) of a sample to be classified and a plurality of respective error estimates ( 104 ) of respective ones of the plurality of numerical features; a statistical module ( 106 ) for associating respective probability density functions ( 108 ) with the respective ones of the plurality of numerical features, wherein the respective probability density functions depend on the respective error estimates of the respective numerical features; a replication module ( 110 ) for producing a plurality of perturbed replicas ( 112 ) of the sample, the perturbed replicas comprising perturbed features, wherein the respective ones of the plurality of numerical features are randomly perturbed according to the corresponding respective probability density functions to obtain the perturbed features; a classifier ( 114 ) for classifying respective ones of the plurality of perturbed replicas based on the perturbed features and by applying predetermined classification criteria to obtain classified replicas ( 116 ), wherein each classified replica has a class associated therewith; an analyzer ( 118 ) for classifying the sample to be classified based on a statistical analysis of a plurality of the classified replicas ( 116 ) to obtain a sample classification ( 120 ).