1. A method for analysis of data contained in a plurality of spectra generated from a plurality of samples comprising a plurality of different sample classes, the method comprising: aligning the plurality of spectra; constructing a similarity measure for comparing pairs of samples; training at least one support vector machine to discriminate between the plurality of different sample classes, wherein the at least one support vector machine comprises a kernel; processing the plurality of spectra using the at least one support vector machine; identifying at least one predictive feature within the plurality of spectra.