Protein phosphorylation is a common post-translational protein modification used in almost all cellular processes. When a phosphate group is added to an amino acid side chain, it may alter the protein conformation and protein-protein interactions due to its size and its negative charge. It may also change the protein function, activity and even localization within the cell. Experimental detection of phosphorylation is still extremely labor demanding and very expensive, even when deploying protein mass spectrometry. For this very reason many bioinformatics scientific groups focus on the prediction of protein phosphorylation sites. Recent analyses of phosphorylation sites studied mainly non-phosphorylated phosphorylation sites and the distribution and representation of amino acids sequentially neighboring them. Since sequentially more distant, but structurally close amino acids can contribute to the recognition of protein substrate by protein kinase, structural environment of phosphorylation sites was studied in this thesis. Furthermore, 3D structures of phosphorylation sites were comprehensively studied for the first time in a phosphorylated state and the results were compared with the results obtained from the analysis of non- phosphorylated sites. Phosphorylation sites were found mostly within...

This master thesis investigates linkage between personality characteristics and digital records on the Internet. The theoretical part is focused on selected theories of personality traits, brief description of social networks and on current studies connected with relationship between digital records and personality characteristics. Empirical research is dedicated to test interdependences between user profiles at the LinkedIn and Hogan's MVPI and HDS using the research sample (N=238, after reduction N=129 due to limited number of LinkedIn users). Based on LinkedIn data which were reduced to 6 new variables, results describe statistically significant models predicting scores for some scales of MVPI and HDS. However, maximum adjusted R2 was only 15,5% for the best regression model which was predicting Altruistic scale (MVPI).

Práce je rozdělena na tři části. V teoretické části práce jsou přiblíženy významné krize za posledních několik set let, typologie krizí, selhání finančních trhů dle P. Krugmana, generační modely, cenové bubliny, souvislost kapitálových toků a dluhového problému, nákaza, prevence před krizemi a jejich management. V druhé části jsou v rámci popisu současného stavu bádání v oblasti predikce finančních krizí citovány desítky studií. Jejich výsledky jsou následně porovnány. Pozornost je také věnována definici finanční krize. Ve třetí části je provedena aplikace metody Latent Semantic Indexing (LSI) na úlohu predikce finančních krizí. Testovanou hypotézou je předpoklad, že akciové trhy dokáží během jednoho čtvrtletí (64 pozorování akciového trhu) reflektovat budoucí vývoj v měnové politice (během dalších 128 pozorování). Tato hypotéza byla na vzorku 39 zemí, intervalu let 1985 - 2007 a interpretace vývoje úrokových sazeb a měnového kurzu domácí měny vůči USD v disertační práci potvrzena. Uvedená metoda LSI a její studovaná aplikace na akciovém trhu, přestože dokázala nalézt několik krizí i přesně na den, je vhodná spíše pro specifikaci a analýzu křehkých období, kdy ke krizi může dojít, než přímo k předpovídání krizí.

This thesis focuses on data mining technology and its possible practical use in the field of health insurance companies. Thesis defines the term data mining and its relation to the term knowledge discovery in databases. The term data mining is explained, inter alia, with methods describing the individual phases of the process of knowledge discovery in databases (CRISP-DM, SEMMA). There is also information about possible practical applications, technologies and products available in the market (both products available free and commercial products). Introduction of the main data mining methods and specific algorithms (decision trees, association rules, neural networks and other methods) serves as a theoretical introduction, on which are the practical applications of real data in real health insurance companies build. These are applications seeking the causes of increased remittances and churn prediction. I have solved these applications in freely-available systems Weka and LISP-Miner. The objective is to introduce and to prove data mining capabilities over this type of data and to prove capabilities of Weka and LISP-Miner systems in solving tasks due to the methodology CRISP-DM. The last part of thesis is devoted the fields of cloud and grid computing in conjunction with data mining. It offers an insight into possibilities of these technologies and their benefits to the technology of data mining. Possibilities of cloud computing are presented on the Amazon EC2 system, grid computing can be used in Weka Experimenter interface.

The aim of this study is to certify the legitimacy of employing quantitative methods in the day-to-day business practice. The task is approached as a case study of a real-life financial planning process. I work with the financial data of POS Media Czech Republic (a media company providing point-of-sale advertising solutions). My intention is to simulate the projection of a pro forma income statement with the use of quantitative methods. More specifically, I am applying time series prediction techniques in order to forecast POS Media's sales. The goal is, first, to demonstrate that quantitative techniques can be handled even with limited statistical background and, second, to discuss the relevancy of the obtained results. In the methodical part of my thesis I deal with the theoretical aspects of financial planning. I further describe various methods of sales forecasting (qualitative vs. quantitative). Special emphasis is put on time series prediction methods. In the application part I provide a short description of POS Media and its business. I use time series decomposition techniques to predict POS Media's sales in 2012. Consequently, I outline the rest of the pro forma income statement.

Thesis deals with complex process of creation of new bankruptcy model for predicting business failure, while this process involves selection of quality sample, verification of classification accuracy of already existing bankruptcy models, profile analysis and finally the derivation of specific equation of bankruptcy model. The derivation is performed by using two selected statistical methods, discriminant analysis and logistic regression. Two bankruptcy models Bürger's index DA12 and Bürger's index LR12 were derived by using the mentioned statistical methods. The new models distinct advantage is, unlike already existing and renowned bankruptcy models, that they are focused on classification of micro and small enterprises in terms of Czech Republic, while classification accuracy one year before failure is by individual models 74.8 % and 81.87 %. Derived models have clear interpretation (no grey zone) and easy calculation, which brings a possibility for micro and small entrepreneurs to check their business partners in terms of failure prediction.

This diploma thesis deals with the possibilities of prediction of specific learning disabilities among children of preschool age. The thesis is divided into two consequent parts a theoretical part and a practical part. In the theoretical part I focus mainly on the etiology and the diagnosis of specific learning disabilities. The thesis focuses mainly on given examples of a few predictive batteries from Czech and even foreign authors. The practical part contains results of a research survey where are the data I collected through predictive battery of British authors: Nicolson and Fawcett: The Dyslexia Early Screening Test. The main objective of the diploma thesis was to find out the possibility of using this test by pedagogical workers at pre-schools in order to avoid specific learning disabilities. For the research, the quantitative research method was used.

In this work was evaluated the effectiveness of artificial neural networks in trading on the stock markets. The subject of the work was the process of optimizing parameters of artificial neural networks, the resulting predictive efficiency was determined on the basis of the application being optimized parameters of neural networks.

Improving the short-term results of kidney transplantation did not result in improving the long-term function and survival of kidney allograft. Organ shortage and increasing number of marginal donors remains the key problem in transplant today. The quality of donor organ is critical for graft function development and survival. The aim is to improve understanding to ischemia/reperfusion injury and its consequences, predict delayed graft function and rejection, improve organ allocation strategy and identify patients suitable for safe drug minimization or complete withdrawal of immunosuppressive therapy. Analysis of donor kidneys identified poor tubular cell quality and low survival factor, Netrin-1 expression levels, to be associated with delayed graft function. We confirmed that reperfusion phase of ischemia/reperfusion injury leads to minimal morphological but significant molecular abnormalities. Dissociation observed in histology and molecular pathology finding calls for an integrated approach in donor quality organ evaluation and allocation for transplantation. Significant heterogeneity within donors with expanded criteria was shown and subgroup of organs at low risk of delayed graft function was identified. We suggested donor biopsies to be performed as a routine praxis in all kidneys...

The thesis „The Inventory Management of Trading Company” deals with the issue of material flow and inventory management. In the introductory part of the thesis, the theoretical basis of supply logistics in a logistics chain, the issue of inventory, its storage and in particular its management have been defined. In the second part, inventory management in a logistics center of a company has been analyzed. In the last part, the solutions for improving inventory management of a company, mainly in terms of reduction of the amount, have been proposed.