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Fyzikálně-chemická charakterizace peptidů a bílkovin kapilárními elektromigračními metodami
Kašička, Václav ; Koval, Dušan ; Šolínová, Veronika ; Sázelová, Petra ; Prusík, Zdeněk
High-performance capillary electromigration methods, zone electrophoresis, isotachophoresis, isoelectric focusing, affinity electrophoresis and electrokinetic chromatography, are presented as powerful tools for physicochemical characterization of peptides and proteins.
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Statistics of extremes
Fusek, Michal ; Neubauer, Jiří (referee) ; Michálek, Jaroslav (advisor)
The thesis deals with extreme value distributions. The theoretical part is devoted to the basics of extreme value theory and to the characterization of extreme value distributions. There is the limit theorem for distributions of the maximum formulated and characteristics of the extreme value distributions deduced. There are parameter estimates for Weibull, lognormal and exponential distributions inferred using method of maximum likelihood and method of moments. There is also the theory of censored samples described. The practical part is devoted to statistical analysis of rainfall.
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Biodegradation of environmental pollutants - Structural characterization of a new type of haloalkane DbeA
PAPEŽ, Martin
The aim of this work is the crystallization of model protein Xylanase and a new haloalkane dehalogenase DbeA and description of DbeA structure using modeling programs. For this purpose, the crystallization methods based on sitting and hanging drop vapor diffusion, crystallization under oil and crystallization in capillaries were applied. The structure was solved using programs WinCoot and VMD. The results will be used for further research of structure-functional relationships of haloalkane dehalogenases.
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Feasibility Study of an Interactive Medical Diagnostic Wikipedia
Grim, Jiří
Considering different application possibilities of product distribution mixtures we have proposed three formal tools in the last years, which can be used to accumulate decision-making know-how from particular diagnostic cases. First, we have developed a structural mixture model to estimate multidimensional probability distributions from incomplete and possibly weighted data vectors. Second, we have shown that the estimated product mixture can be used as a knowledge base for the Probabilistic Expert System (PES) to infer conclusions from definite or even uncertain input information. Finally we have shown that, by using product mixtures, we can exactly optimize sequential decision-making by means of the Shannon formula of conditional informativity. We combine the above statistical tools in the framework of an interactive open-access medical diagnostic system with automatic accumulation of decision-making knowledge.
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