Abstract: The invention relates to a method to evaluate mass spectrometry data for the analysis of peptides from biological samples, particularly MALDI-TOF mass spectrometry data, comprising the steps of: providing expected mass defects; determining measured mass defects, i.e. the mass defects resulting from the mass spectrometry data; and comparing the measured mass defects with the expected mass defects.

Abstract: The disclosure relates to a method for processing a mass spectrum, comprising: (i) providing the mass spectrum which contains a plurality of data pairs, each data pair being representative of a mass value or mass-related value on a mass scale or mass-related scale and an abundance value or abundance-related value associated with the respective mass value or mass-related value, (ii) selecting a plurality of intervals on the mass scale or mass-related scale, each interval containing a multitude of the said data pairs, (iii) for each interval, applying a first mathematical-statistical analysis to the said data pairs contained in the respective interval in order to derive an interval-specific peak width, and (iv) using the said interval-specific peak widths to determine an estimated peak width for each mass value or mass-related value on the mass scale or mass-related scale.

Abstract: The invention relates to a method to evaluate mass spectrometry data for the analysis of peptides from biological samples, particularly MALDI-TOF mass spectrometry data, comprising the steps of: providing expected mass defects; determining measured mass defects, i.e. the mass defects resulting from the mass spectrometry data; and comparing the measured mass defects with the expected mass defects.

Abstract: The disclosure relates to a method for processing a mass spectrum, comprising: (i) providing the mass spectrum which contains a plurality of data pairs, each data pair being representative of a mass value or mass-related value on a mass scale or mass-related scale and an abundance value or abundance-related value associated with the respective mass value or mass-related value, (ii) selecting a plurality of intervals on the mass scale or mass-related scale, each interval containing a multitude of the said data pairs, (iii) for each interval, applying a first mathematical-statistical analysis to the said data pairs contained in the respective interval in order to derive an interval-specific peak width, and (iv) using the said interval-specific peak widths to determine an estimated peak width for each mass value or mass-related value on the mass scale or mass-related scale.

Abstract: The invention relates to a method to evaluate mass spectrometry data for the analysis of peptides from biological samples, particularly MALDI-TOF mass spectrometry data, comprising the following steps: a) provide expected mass defects; b) determine measured mass defects, i.e. the mass defects resulting from the mass spectrometry data; c) compare the measured mass defects with the expected mass defects.

Abstract: The invention relates to a method to evaluate mass spectrometry data for the analysis of peptides from biological samples, particularly MALDI-TOF mass spectrometry data, comprising the steps of: providing expected mass defects; determining measured mass defects, i.e. the mass defects resulting from the mass spectrometry data; and comparing the measured mass defects with the expected mass defects.

Abstract: The invention relates to methods for processing ion-spectrometric measurement signal data which are recorded spatially resolved across a two-dimensional sample, comprising: —providing the measurement signal data which have a plurality of measurement signal histograms, where a histogram contains a measurement signal tuple with intensity dimension (J), mass dimension (m), and collision cross-section dimension (?), or quantities derived therefrom; —specifying first and second selections of ionic species for the sample, whose presence in histograms is detectable and distinguishable using the collision cross-section dimension or proxy; —determining the spatially resolved content of ionic species from the first and second selections in histograms of the finite areas (Afin,x,y), and computing the various contents to form spatially resolved content scores (Gx,y); and —labeling the sample with the content scores (Gx,y).

Abstract: The disclosure relates to a method which is suitable for the quality control and signal correction of mass spectrometry data of biological tissue samples and is based on the analysis of the chemical background signal observed in a spectrum. It exploits the fact that the chemical background signal contains components from a plurality of polymer molecules, whose chemical structure has strong regularities. These regularities mean that the observed masses are subject to certain statistical distributions, which are each characteristic of the class of molecule. By analyzing these statistical properties, it is possible to detect and correct any mass shifts which may be present.

Abstract: The disclosure relates to a method which is suitable for the quality control and signal correction of mass spectrometry data of biological tissue samples and is based on the analysis of the chemical background signal observed in a spectrum. It exploits the fact that the chemical background signal contains components from a plurality of polymer molecules, whose chemical structure has strong regularities. These regularities mean that the observed masses are subject to certain statistical distributions, which are each characteristic of the class of molecule. By analyzing these statistical properties, it is possible to detect and correct any mass shifts which may be present.

Abstract: A number of standard methods exist for normalizing MALDI-TOF data, but they are not able to compensate adequately for the observed technical variability. The invention creates an improved normalization method for MALDI-TOF mass spectrometry data. This is achieved by an intensity profile normalization, where, by way of example, 1) Firstly, an intensity profile is formed for each individual spectrum, and this intensity profile describes the statistical distribution of the intensity values within different mass ranges; 2) Then an average reference profile is formed for an ensemble of spectra; 3) Finally, the individual spectra are transformed in such a way that their intensity profiles correspond to the reference profile.

Abstract: The invention relates to a method to evaluate mass spectrometry data for the analysis of peptides from biological samples, particularly MALDI-TOF mass spectrometry data, comprising the following steps: a) provide expected mass defects; b) determine measured mass defects, i.e. the mass defects resulting from the mass spectrometry data; c) compare the measured mass defects with the expected mass defects.

Abstract: A number of standard methods exist for normalizing MALDI-TOF data, but they are not able to compensate adequately for the observed technical variability. The invention creates an improved normalization method for MALDI-TOF mass spectrometry data. This is achieved by an intensity profile normalization, where, by way of example, 1) Firstly, an intensity profile is formed for each individual spectrum, and this intensity profile describes the statistical distribution of the intensity values within different mass ranges; 2) Then an average reference profile is formed for an ensemble of spectra; 3) Finally, the individual spectra are transformed in such a way that their intensity profiles correspond to the reference profile.