This diploma thesis includes an experimental and a bioinformatic part. The two parts are linked together through the subject of transcription factors of 'forkhead box O' (FOXO) family. FOXO transcription factors have a key role in many cellular processes including cell cycle regulation, apoptosis and metabolism. For a long time, they have been considered strictly as the tumor-suppressors yet a growing number of evidence is pointing out to their pro-tumorigenic role. In consequence FOXO transcription factors are studied intensively as potential therapeutic targets in cancer. In the past decade, in silico prediction of protein-protein interactions has become popular in basic research as well as in drug development. Nonetheless, the predicted structures are still far from fitting to the expected behavior of the respective biomolecules. In the experimental part of this thesis, I verified the interaction of four in silico predicted protein binders based on naturally occurring PDZ domain with FOXO4 using microscale thermophoresis. Non-invasive bladder tumors represent a heterogeneous disease where reliable prediction of tumor aggressiveness is still lacking despite an intensive research. In the bioinformatic part of this thesis, I described the cellular composition of the tumor microenvironment and demonstrated...

This master's thesis deals with knowledge discovery in databases, especially basic methods of classification and prediction used for data mining are described here. The next chapter contains introduction to multimedia databases and knowledge discovery in multimedia databases. The main goal of this chapter was to focus on extraction of low level features from video data and images. In the next parts of this work, there is described data set and results of experiments in applications RapidMiner, LibSVM and own developed application. The last chapter summarises results of used methods for high level feature extraction from low level description of data.

The goal of this work is to create data mining module for information system Belinda. Data from database of clients will be analyzed using SAS Enterprise Miner. Results acquired using several data mining methods will be compared. During the second phase selected data mining method will be implemented such as module of information system Belinda. The final part of this work is evaluation of acquired results and possibility of using this module.

This master's thesis is dedicated to theme of knowledge discovery in Multimedia Databases, especially basic methods of classification and prediction used for data mining. The other part described about extraction of low level features from video data and images and summarizes information about content-based search in multimedia content and indexing this type of data. Final part is dedicated to implementation Gaussian mixtures model for classification and compare the final result with other method SVM.

The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.

This thesis summarizes knowledge in the field of time series theory, method for time series analysis and applications in financial modeling. It also resumes the area of evolutionary algorithms, their classification and applications. The core of this work combines these knowledges in order to build a system utilizing evolutionary algorithms for financial time series forecasting models optimization. Various software engineering techniques were used during the implementation phase (ACI - autonomous continual integration, autonomous quality control etc.) to ensure easy maintainability and extendibility of project by more developers.

Tato práce pojednává o vytvoření mobilní aplikace zvažující kontext zařízení, která vybírá a doporučuje hudební skladby dle aktuálního stavu kontextu zařízení. Kontext je získáván na základě naměřených hodnot, které jsou získány z vestavěných senzorů mobilního zařízení a z ostatních systémových hodnot zařízení. Výběr konkrétní skladby je poté založen na výstupu modelu strojového učení, který klasifikuje kontext na základě aktuálních získaných dat a následně zvolí skladbu připadající k danému kontextu.

Thesis "Data Mining in the Field of English Football League Third Division's Betting Odds" deals with data mining referring to acquiring knowledge from data. The main objective of this work is to develop data models for prediction of match results and to compare these predictions with a chosen strategy of betting. The selected betting strategy is based on betting single bets with odds belonging to chosen intervals, which generate a profit. These odds intervals were discovered by analyzing 2006-2009 football matches in a created simulator. On the basis of these odds ranges data models were constructed. Each data model contains a hypothesis which is generated by SD4ft procedure of LispMiner based on all football matches played in seasons 2001-2008. Developed data models are tested afterwards using 2006-2009 football matches data. Results show that all derived data models are profitable in all four seasons under consideration. More than half of them successfully predicted 2009 matches as well. The analysis showed that betting agencies offer mostly odds which make it almost impossible to be profitable while betting on matches according to their odds. In spite of this fact I identified some odds intervals with which you can success while betting single bets on home-team, draw or visitor-team with odds falling within these intervals. Association rules with reasonable confidence and support can generate high profitability. It is important to realize that there are no data models which guarantee a certain profit. Most of developed data models are not applicable in the real world, some of them can actually generate a loss. Nevertheless there are data models to be found that could generate a profit in the real world.

Theory: - Controlling - its function and structure - Costs Analytical part: - Cost variance tracking and evaluation of its monthly prediction - Proposal of best practices for cost variance prediction done on monthly basis

The times coming with the End of the Cold War were very turbulent. Politicians had to take into the consideration lots of scenarios and the next global trends to make correct decisions. Most of the very numerous visions of the future global order followed more or less the twofold pattern: order or anarchy. "The End of History and the Last Man" and "The Clash of Civilizations and the Remaking of World Order" written by two prominent American political scientists Francis Fukuyama and Samuel P. Huntington and published at the beginning of the 90s are the most representative works that fit into this pattern. These provocative and controversial theories have been criticized and empirically challenged by many on one side, on the other side it hasn't impeded others to use them as a starting point for their next analyses. This dissertation thesis is a contribution to the debate between the dissenters and the supporters of these theories from a predictive point of view. Through the research theoretical methodology it is argued that the examined theories are still valid even nowadays because their theoretical essence (or hard core in the Lakatosian research program) has not been refuted yet. Nevertheless, the hard core of the theories determines their very specific character which puts forward the importance of the factors labelled in the Lakatosian framework as an external history of a science. These factors organized according to the Mehtas criteria of so called strong idea are, especially in the social sciences, decisive for how a theoretical construct is accepted in a broader non-academic context. It is demonstrated that both theories fulfill all criteria to be very influential in practice, although the idea of clash of civilizations is even more powerful in this respect. The specific features of all theories are illustrated on two case studies: Union of South American Nations and Shanghai Cooperation Organization. Firstly, the selection of these case studies is justified and secondly, the anomalies in terms of the Lakatosian methodology are identified and then explained. There have been found no unexplainable anomalies, which practically confirms the validity of both research programs on one side, on the other side it facilitates a better assessment of the studied theories in a sense of their interpretative scope and possibilities.