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Abstract: The new generation of mass spectrometers produces an astonishing amount of high-quality data in a brief period of time, leading to inevitable data analysis bottlenecks. Automated data analysis algorithms are required for rapid and repeatable processing of mass spectra containing hundreds of peaks, the part of the spectra containing information. New data processing algorithms must work with minimal user input, both to save operator time and to eliminate inevitable operator bias. Toward this end an accurate mathematical algorithm is presented that automatically locates and calculates the area beneath peaks. The promising numerical performance of this algorithm applied to raw data is presented. [Copyright &y& Elsevier]

MassSpectator is a novel suite of numerical algorithms that accurately locates and calculates the area beneath peaks from real mass spectral data by using only reproducible mathematical operations. It requires no user-selected parameters but does require a background spectrum to determine instrumental noise. Such a fully automated algorithm is useful for rapid and repeatable processing of mass spectral data containing hundreds of peaks. MassSpectator represents a first attempt to create an unbiased method using time series segmentation to analyze mass spectral data.