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LC-MS analysis based on probabilistic approach
URBAN, Jan
Liquid chromatography (LC) in tandem with mass spectrometry (MS) is a measurement tool for obtain information about the compounds in the investigated extracts. There were already developed methods for processing and analysis of measured data sets. However, only partial problems of processing/analysis task were handled independently. Therefore, the rst part describes existing methods and techniques commonly used in the LC-MS for the processing and analysis today. In this thesis an approach based on the theory of systems is used for description of abstract model above the measured data. This model encapsulated all processing/analysis steps into appropriate and consistent mathematical space. The creation of this model via description of the measurement device and data outputs is introduced. Abstract model of LC-MS data set is used to decompose the measurement into three partial contributions, the analyte signal, the random noise and the systemic noise. The separation process of the signal could be estimated using the probabilistic approach. That probabilistic approach to the LC-MS analysis was implemented in the developed software, which was published in the Bioinformatics Journal.
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Měření vnitřní difuze pomocí kapalinové chromatografie
Soukup, Karel ; Schneider, Petr ; Šolcová, Olga
Liquid chromatography setup was used in liquid diffusion studies. The Kubin-Kucera model was employed for mathematical description of processes inside the chromatographic column. Effective diffusivities were evaluated by time-domain fitting chromatographic response peaks of columns packed with tested porous particles. Axial dispersion coefficients were determined independently by analysis of response peaks of columns packed with nonporous pellets; this improved significantly the confidence of effective diffusion coefficients. An attempt was made to exclude the end effects of chromatographic columns by analyzing response peaks of pairs of columns differing by lengths.
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