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In silico prediction of postranslational modifications
Basíková, Iveta ; Novotný, Marian (advisor) ; Fišer, Karel (referee)
Post-translational modifications are an important form of cellural regulation, including matabolism, growth, differentiation, transcription activation, membrane transport and cell death. Experimental identification of post-translational modifications (PTMs), especially phosporylation, is still time consuming and expensive. Progress in silico PTM prediction tools was influnced an enormous growth of known sequences which are suitable for training set, processing and final result's interpretation. In silico prediction may facilitate the identification of potencional phosporylation sites and it may speed up in future research.
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Neuroactive steroids and addictions
Jandíková, Hana ; Vondra, Karel (advisor) ; Miovský, Michal (referee) ; Kršek, Michal (referee)
Neuroactive steroids are a group of steroid hormones which act non-genomically to influence the neuron excitability of neuronal synapses. Addictive substances can interfere with the synthesis of neuroactive steroids through many mechanisms, affecting their levels and changing their functionality. At the same time, neuroactive steroids play a role in the development of addiction, since their levels change during attempts to quit and therefore affect the success of treatments for addiction. This study focuses on the relationships between individual addictive substances and neuroactive steroids, the individual functional mechanisms and how they influence each other. It is generally known that addictive substances result in the release of anxiolytics that act on neuroactive steroids. This plays a role in the development of addiction. We also describe in detail the effect of smoking on steroid hormones and the endocrine system in general. Using tobacco addition as a model, we studied the relationship between addiction and neuroactive steroids. As part of my doctoral studies we performed a prospective study that followed changes in the steroid spectra induced by smoking as well as when quitting smoking. We also developed a predictive model to predict the likelihood of success in treating tobacco...
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Assessing Selected Indicators Using Statistical Methods
Lovas, Jakub ; Hájek, Michal (referee) ; Doubravský, Karel (advisor)
The bachelor thesis deals with the assessment of selected indicators of SAKO Brno a.s. using statistical methods. Theoretical starting points describing selected indicators and statistical methods are presented in the first part of thesis. The practical part contains the calculations of the individual indicators for the period from 2009 to 2015, which are necessary for the development of own solutions proposals. The bachelor thesis also includes a simple application created in Microsoft Office Excel 2016.
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Bankruptcy Prediction Modelling in the Agriculture Business
Pokorný, Petr ; Peter,, Markovič, (referee) ; Karas, Michal (advisor)
This master’s thesis is focused on problematic within the prediction of bankruptcy of companies operating in the field of agriculture in Czech republic. First part consists of introduction to companies that do business in field of agriculture and it describes bankruptcy models that are used in academicals sphere. Other part of thesis is divided into two sub-parts. First part is dedicated to an application of data into models of bankruptcy and their evaluation. Second part is focused on improvement of the best model and its main goal is to maximize the precision of the bankruptcy.
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Tribotechnical diagnostics of oils
Pokorný, Ondřej ; Frýza, Josef (referee) ; Svoboda, Petr (advisor)
The purpose of this bachelor’s thesis is compile an overview of currently used sensors for real-time oil analysis. The paper contains a record of knowlenge in field of wear and tribotechnical sensors and determines the appropiate behavior of the tribological system for predictive maintenance. In the next part of the thesis are evaluated the introduced sensors and with help of obtained informations is assembled diagnostic for monitoring the state of gearbox of wind power plants.
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Assessing Selected Indicators Using Time Series Analysis
Travencová, Darina ; Mach, Zdeněk (referee) ; Doubravský, Karel (advisor)
The master´s thesis evaluates the economic situation of the company SCHWARTZ TECHNICKÉ PLASTY ČR s. r. o. using statistical methods. The theoretical part describes the issues necessary for the practical part, financial indicators, time series, regression and correlation analysis. In the practical part is an analysis of selected indicators of financial analysis, then statistical methods are used to predict future developments for the coming two years and to detect dependencies between the indexes. The last section contains suggestions for improving the current situation, which are based on calculations from the practical part.
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Assessment of the effect selected investments on the financial situation of enterprise
VALDMANOVÁ, Dominika
The investment and the decision about them are one of the most important activities in the company. The deci-sion can significantly affect the company. Bad decision can cause a bankruptcy in the worst case. Other way the good decision can cause in the future growth and development. It is very important for the company to make a good decision. The company can compete better. The company XYZ, whose data are choosen in the bacheleor thesis, make decision for the investment to the fixed asset specially the extension of the production hall. It increases the volume of manufactured products. The realization of the hall is financed from the subsidy of Ministry of Industry and Trade. The subsidy covers one third of the price. The rest is paid from the bank loan. In the work there are described the pre-investment preparation, different ways of investments and cases of invest. There are described the methods of evaluating the effectiveness of investments. In the second practical part there is counted the effectiveness of the specific investment. Then there is created the prediction to the future. In the end of the work the prediction is compared with the real status, which occurred in the company.
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Robust Regression Estimators: A Comparison of Prediction Performance
Kalina, Jan ; Peštová, Barbora
Regression represents an important methodology for solving numerous tasks of applied econometrics. This paper is devoted to robust estimators of parameters of a linear regression model, which are preferable whenever the data contain or are believed to contain outlying measurements (outliers). While various robust regression estimators are nowadays available in standard statistical packages, the question remains how to choose the most suitable regression method for a particular data set. This paper aims at comparing various regression methods on various data sets. First, the prediction performance of common robust regression estimators are compared on a set of 24 real data sets from public repositories. Further, the results are used as input for a metalearning study over 9 selected features of individual data sets. On the whole, the least trimmed squares turns out to be superior to the least squares or M-estimators in the majority of the data sets, while the process of metalearning does not succeed in a reliable prediction of the most suitable estimator for a given data set.
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Utilization of Data Mining for Personnel Agency
Ondruš, Erik ; Janata, Michal (referee) ; Luhan, Jan (advisor)
This master’s thesis will look into the use of data mining in the area of segmentation and the prediction of onboarding candidates of a recruitment agency. The obtained results should serve to make company processes more effective concerning the processing of orders, and should also facilitate a more personal approach to candidates. The first chapter includes imperetive theoretical bases from the studies of Business Intelligence, data warehouses, data mining and marketing. Thereafter an analysis of the current state is presented with a focus on the capture of the key processes in processing and order. The last chapter looks at the proposed solution and implementation on the platform Microsoft SQL Server 2014. To conclude there are proposals of utilizing data mining in direct marketing.
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