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Fragments of Landscape
Nováková, Kateřina ; Gajdošíková, Pavla (advisor) ; Sedlák, Michal (referee)
The master thesis Fragments of Landscape explores the meaning of landscape in contemporary Czech art, using an a/r/tographic approach focused on exploring artistic and pedagogical practice through artistic production. Emphasis is placed on the importance of connecting the roles of artist, researcher and teacher. The first part of the thesis introduces the method of a/r/tography, explores the definition of landscape and the characteristics associated with its value, and the contemporary artistic view of landscape within the contemporary Czech art scene. It analyses artistic approaches to landscape and classifies them into nine categories, reflecting the diverse artistic approaches, the author's view of landscape and their influence on the creation and understanding of landscape. The author's own artistic work focuses on the authorial process of landscape transformation and interpretation, based on art field research of the Jizera Mountains and the resulting creation of a network of landscape fragments. The categorization of artistic approaches is the key to understanding the complexity of the creative process. The categorisation implies that the landscape cannot be clearly framed and categorised. The thesis concludes by evaluating the importance of didactic tasks in the process of art education,...
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History of the Czech minority school in Zátoň in the years 1920 1950
KELLINGEROVÁ, Michaela
The main goal of the work is to describe the life of the Czech minority school in Zátoň from 1920 to 1950 and its changes in the context of that period. The introductory part describes the geography and history of the village. The following chapters focus on the period of the First Republic, the period of Nazi occupation, and the post-war period until 1950. In the following chapters a brief description of the period, Czech-German relations, the development of education, and a description of life at the Czech school in Zátoň are given. Direct, indirect, and comparative methods were used in the historical research. The primary source of information was contemporary sources and professional literature. The state establishment and the geographical location of the village influenced the running of the school.
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Analysis of DNA Structure Elements
Knytl, Marek ; Burgetová, Ivana (referee) ; Martínek, Tomáš (advisor)
The aim of this master's thesis is the design and implementation of tool trackAnalysis for statistical analysis of DNA structure elements. The positions of individual elements in genome are obtained in the form of the track, and with these positions the tool performs a set of analyzes, including randomness test of track, test examining distances between track and genes, detection of clusters and overlaps. The indivudual tests results can be linked together. The results will be displayed in the form of a list, a graph or a new annotation track. An important part of this thesis is also testing the resulting tool on a set of real data.
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Whole genome alignment using suffix trees
Klouba, Lukáš ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
The aim of this thesis is to create an algorithm that allows the alignment of the genome of two organisms by means of suffix structures and to implement it into the programming language environment R. The thesis deals with the description of the construction of the suffix structures and the methods of whole genome alignment. The result of the thesis is a functional algorithm for whole genome alignment by means of suffix structures implemented in the software environment R and its comparison with similar programs for the whole genome alignment.
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Data Mining with Python
Šenovský, Jakub ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The main goal of this thesis was to get acquainted with the phases of data mining, with the support of the programming languages Python and R in the field of data mining and demonstration of their use in two case studies. The comparison of these languages in the field of data mining is also included. The data preprocessing phase and the mining algorithms for classification, prediction and clustering are described here. There are illustrated the most significant libraries for Python and R. In the first case study, work with time series was demonstrated using the ARIMA model and Neural Networks with precision verification using a Mean Square Error. In the second case study, the results of football matches are classificated using the K - Nearest Neighbors, Bayes Classifier, Random Forest and Logical Regression. The precision of the classification is displayed using Accuracy Score and Confusion Matrix. The work is concluded with the evaluation of the achived results and suggestions for the future improvement of the individual models.
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MHC and KIR genotyping of macaques in HIV infection research
Matula, Jan ; Maděránková, Denisa (referee) ; Sedlář, Karel (advisor)
Modern research of viral diseases relies on genomic data processing. Not only is the sequence of a virus important, genomic sequence of specific receptors in affected organisms also plays an important role. In this paper, a novel package for processing of next generation sequencing data in infectious disease written using R/Bioconductor language is proposed. Functionality of the package, including implementation of advanced SSAHA algorithm for fast database searches, is demonstrated using genotyping of genes for MHC and KIR receptors of HIV positive macaques.
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Optimization of Algorithms for Triplex Detection
Hon, Jiří ; Bendl, Jaroslav (referee) ; Martínek, Tomáš (advisor)
Triplex-forming DNA sequences have been implicated as important players in several key processes, such as transcriptional regulation, DNA recombination and mutagenesis, which emphasize their importance for biology, biotechnology and medicine. This bachelor thesis optimizes recently publicated dynamic programming algorithm for identification of triplex-forming sequences on three levels of design: user interface, memory usage and computation time. On the level of user interface, the algorithm was extended with existing visualization functions and rewritten into R/Bioconductor package. Memory usage optimization and processor cache analysis in combination with computation time reduction based on current computation state analysis lead to more than three times acceleration.
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Molecular Signature as Optima of Multi-Objective Function with Applications to Prediction in Oncogenomics
Aligerová, Zuzana ; Maděránková, Denisa (referee) ; Provazník, Ivo (advisor)
Náplní této práce je teoretický úvod a následné praktické zpracování tématu Molekulární signatura jako optimální multi-objektivní funkce s aplikací v predikci v onkogenomice. Úvodní kapitoly jsou zaměřeny na téma rakovina, zejména pak rakovina prsu a její podtyp triple negativní rakovinu prsu. Následuje literární přehled z oblasti optimalizačních metod, zejména se zaměřením na metaheuristické metody a problematiku strojového učení. Část se odkazuje na onkogenomiku a principy microarray a také na statistiku a s důrazem na výpočet p-hodnoty a bimodálního indexu. Praktická část je pak zaměřena na konkrétní průběh výzkumu a nalezené závěry, vedoucí k dalším krokům výzkumu. Implementace vybraných metod byla provedena v programech Matlab a R, s využitím dalších programovacích jazyků a to konkrétně programů Java a Python.
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Cluster Analysis Czech 100 Companies on the Basis of Financial Statements
Langer, Tomáš ; Král, Jiří (referee) ; Novotná, Veronika (advisor)
The diploma thesis called Cluster Analysis Czech 100 Companies on the Basis of Financial Statements deals with the testing of two hypotheses using a multidimensional statistical method - cluster analysis. The input data for the application of statistical methods are financial statements of selected companies for the years 2014 and 2015 which are publicly available. These data are digitized and subjected to methods of financial analysis.
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