Prediction and searching for homologous protein sequences is one of important tasks which are currently being addressed in the area of bioinformatics. According to the determination of homologous sequences of unknown protein sequence it is often possible to determine its structure and function in the organism. For searching homologous sequences, the most frequently used tools are based on direct sequence comparison, profile comparison or on the use of hidden Markov models. There is no universal method better than all others. To satisfy user`s request on needed sequence identity between domains and error rate between founded true positive and false positive pairs, the selection of proper method and its settings is needed. This work is focused to create tool which will help user to choose the best method and its settings according to his requirements. It was created on the basis of the analysis of method results with different settings. In addition, the implemented  application offers the possibility to run this method and show its results.

This master's thesis deals with the matter of predicting the effects of aminoacid substitutions on protein stability. The main aim is to design meta-classifier that combines the results of the selected prediction tools. An evolution strategy was used to find the best weights for each of the selected tools with the aim of achieving better prediction performance compared to that achieved by using these tools separately. Five different and obtainable prediction tools were selected and their prediction outputs were weighted. Two different approaches of evolution strategy are investigated and compared: evolution strategy with the 1/5-rule and evolution strategy with the type 2 of control parameters self-adaptation. Two independent datasets of mutations were created for training and evaluating the performance of designed meta-classifier. The performed experiments and obtained results suggest that the evolution strategy could be considered as a~beneficial approach for prediction of protein stability changes. However, the special attention must be paid to careful selection of tools for integration and compilation of training and testing datasets.

The thesis deals with the analysis of the macroeconomic, market and intern environment of corporations in order to analyze the appropriate time to establish a new company or to invest into an existing economical subject. For this purpose the qualitative modeling was used. Thanks to this method there is a possibility to predict the future development of the factors that have an influence on rentability of companies. The choice of variables is the same as with the ones that are analyzed in the process of evaluation rating.

This master´s thesis deals with the assessment of selected comany indicators using time lines. It contains theoretical statements describing the problems of time lines, regression analysis and correlation analysis. Practical part focuses on application of theoretical statements, in another words using the fomulas and graphical representation of selected economical indicators. Suggestions on improving the current situation of company are proposed based on the relults.

Modelling of interactions of proteins and peptides with metal ions Ondrej Gutten - Diploma thesis Keywords: Metalloproteins, metal ion selectivity, in silico prediction Abstract: An approach for in silico prediction and estimation of selectivity properties of metal-binding peptides is suggested. An in-depth analysis is performed to disclose the justifiability and limitations of this approach. The study is divided into three parts. First part investigates the soundness of two quantum chemical methods (MP2 and DFT) for their use in the set-up quest. The testing includes comparison with CCSD(T), effect of basis selection, performance of the two methods in geometry optimizations and effect of implicit solvent model. Second part foreshadows the approach of searching for a metal selective peptide by thoroughly investigating the ability of simple representative systems, derived from their metalloprotein templates, to retain the property of interest. Final part describes the initial step of extensive combinatorial approach towards examination of vast number of simple systems that represent metal-binding sites, and which are to be used for prediction of metal-selectivity through exploitation of the described approach and, ultimately, to the de novo design of metalloproteins with desired properties.

Predikce rizika rozvoje akutního koronárního syndromu na základě neinvazivních vyšetření ABSTRACT The aim of presented diploma thesis coming out of the project held by II. interní klinika Všeobecná fakutní nemocnice v Praze is to determinate the risk assessment for development of acute coronary syndrome based on non-invasive examinations - intracoronary ultrasound, retinal arteries examination, biochemical markers of atherosclerosis and selected genes polymorphism. The thesis is divided into two main parts. The first part is theoretical and it consists of three chapters, the second part is analytical and it contains the research. The theoretical part gives concise information about the acute coronary syndrome, essential part focuses on atherosclerosis as a pathophysiologic base of this syndrome, risk factors, and stratification of cardiovascular risk which proved to be insufficient are as well mentioned. Next part describes a non-invasive coronary arteries examinations focusing on presented research. The last chapter of the theoretical part focuses on invasive coronary arteries examinations. The research part describes design and purpose of the project - the identification the high risk for development of acute coronary syndrome patients irrespective of the risk coming out standard evaluation models, and...

Nowadays, electricity production from photovoltaics power plants is becoming important increasingly. In order to set production to other power plants, it is necessary to predict the generation of electricity from these sources. The thesis is mainly devoted to models for short-term prediction, which is based on weather forecast. The models were designated by beta regression and linear regression with transformed explanatory variable. One part of thesis is devoted to Clear sky model, which is used to estimated the maximum possible production at given hour. 1

Introduction: Achondroplasia is the most common bone dysplasia. It is caused by mutations in the FGFR3 gene, which is involved in regulation of proliferation and maturation of chondrocytes on the growth plates. Activating mutation results in impaired endochondral ossification and a wide range of symptoms: severe growth disorder with limb shortening, macrocephaly with risk of hydrocephalus, mid-facial dysplasia, sleep apnea, narrowing of the spinal canal, increased risk of respiratory complications, and airway inflammation. The current rapid technological development has led to a better understanding of the processes of epiphyseal growth cartilage, thus enabling the development of new drugs for the treatment of this disorder (modified CNP, soluble FGFR3, meclozine). Nevertheless, current treatment is primarily symptomatic. It is very important to have a growth patterns of patients with achondroplasia who have not been affected by any growth promoting treatment (prolongation surgery, growth hormone). Objectives: The aim of this study is to evaluate the growth of Czech patients with achondroplasia, to compare our data with the world-wide used data by Horton et al. (1978) and the current data by del Pino et al. (2018). The next aim was to verify the accuracy of the multiplier method of final height...

Liver flukes of the family Fasciolidae are parasites of mammals including human. Fascioloides magna and Fasciola hepatica are considered as a veterinary and medically important species occurring also in the Czech Republic. Fascioloides magna and F. hepatica infect wide spectrum of wild and domestic ruminants and in case of F. hepatica human can be also infected. Both flukes are responsible for damage of liver tissue and/or bile-ducts of their definitive hosts causing weight lose, anemia, reduced productivity and in specific cases the death of the host. Effective diagnosis plays the key role in control of F. hepatica and F. magna infections. Current diagnostics is predominantly based on serodiagnostic methods using specific antigens e.g. from excretory-secretory products (ESPs). Due to heterogenity of ESPs, such diagnostic markers can lack the specificity and also the reproducibility of the method is poor. Particular proteins of ESPs are often used in diagnostics of fasciolid flukes. Such approach requires biological material and laboratory procedures associated with identification, purification and antigenicity testing of selected proteins. Recent development of parallel sequencing technologies results in huge amount of genomic, transcriptomic and proteomic data, which are publicly available. Such...

The goal of this thesis is to propose a layer on top of edge-cloud, in order to provide soft real-time guarantees on the execution time of applications. This is done in order to satisfy the soft-real time requirements set by the developers of latency-sensitive applications. The proposed layer uses a predictor of execution time, in order to find combinations of processes with, which satisfy the soft real- time requirements when collocated. To implement the predictor, we are provided with information about the resource usage of processes and execution times of collocated combinations. We utilize similarity between the processes, cluster analysis, and regression analysis to form four prediction methods. We also provide a boundary system of resource usage used to filter out combinations exceeding the capacity of a computer. Because the metrics indicating the resource usage of a process can vary in their usefulness, we also added a system of weights, which estimates the importance of each metric. We experimentally analyze the accuracy of each prediction method, the influence of the boundary detection system, and the effects of weights. 1