Abstract: Methods for processing spectra are disclosed. The method includes obtaining a plurality of spectra, each spectrum in the plurality of spectra comprising a signal including a signal strength as a function of time-of-flight, mass-to-charge ratio, or a value derived from time-of-flight or mass-to-charge ratio. Then, a signal cluster is formed by clustering signals from the plurality of spectra with time-of-flights, mass-to-charge ratios, or values derived from time-of-flights or mass-to-charge ratios that are within a window that is defined using an expected signal width value.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: One embodiment of the invention is directed to a method of processing a plurality of spectra. The method includes receiving values associated with a plurality of sample spots on one or more sample chips, wherein the values were entered using graphic elements representing the sample spots, the graphic elements being displayed on a graphical user interface. Data representing a plurality of signals are received. Each signal in the plurality of signals is annotated with a set of values associated with the sample spot from which the signal is generated.

Abstract: One embodiment of the invention is directed to a method of processing a plurality of spectra. The method includes receiving values associated with a plurality of sample spots on one or more sample chips, wherein the values were entered using graphic elements representing the sample spots, the graphic elements being displayed on a graphical user interface. Data representing a plurality of signals are received. Each signal in the plurality of signals is annotated with a set of values associated with the sample spot from which the signal is generated.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method and system of detecting mass to charge ratio of ions. The method includes producing charged ions in a vacuum, accelerating the charged ions in an electric field into a free flight tube and detecting the charged ions at a detector associated with the free flight tube. A control system selects a bandwidth for filtering a signal produced by the detector and the signal produced by the detector is then filtered with a variable width digital filter based upon the selected bandwidth. The bandwidth for filtering the signal may be selected from a look-up table within the control system based upon the mass to charge ratio of an ion of interest. Alternatively, a peak bandwidth within the signal produced by the detector may be determined and the signal produced by the detector may then be filtered with the variable width digital filter based upon the determined peak bandwidth.

Abstract: A method for calibrating a time-of-flight mass spectrometer is disclosed. The method includes determining the time-of-flight values, or values derived from the time-of-flight values for a calibration substance at each of a plurality of different addressable locations on a sample substrate. Then, one of the addressable locations on the substrate is identified as a reference addressable location. A plurality correction factors are then calculated for the respective addressable locations on the substrate using the time-of-flight value, or a value derived from the time-of-flight value.

Abstract: A method for calibrating a time-of-flight mass spectrometer is disclosed. The method includes determining the time-of-flight values, or values derived from the time-of-flight values for a calibration substance at each of a plurality of different addressable locations on a sample substrate. Then, one of the addressable locations on the substrate is identified as a reference addressable location. A plurality correction factors are then calculated for the respective addressable locations on the substrate using the time-of-flight value, or a value derived from the time-of-flight value.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.