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Tests of Hypotheses in a Set of Spectral Courses Alias Marker Statistics

J. Knizek, J. Sindelar, P. Bouchal, B. Vojtesek, R. Nenutil, L. Beranek, M. Kuba


We describe a universal basic regression algorithm for the identification of marker peak areas in spectral sets. Tests in a set of orthogonal polynomial regressions is the basic principle of this approach. Gnostic cluster analysis is then a very effective algorithmic complement, applicable in the case of excessive behavior of some markers. This new regression algorithm aims at recognition of quantitative dependences of (bio)markers in
general. A special emphasis is put on application in mass spectrometry methods, which has made a great progress in the last 10 years.


Marker Statistics; Spectrometry; Tests of Hypotheses; Mass Spectrometry; SWATH MS.

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