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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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Evolutionary algorithms
Bortel, Martin ; Karásek, Jan (referee) ; Burget, Radim (advisor)
Thesis describes main attributes and principles of Evolutionary and Genetic algorithms. Crossover, mutation and selection are described as well as termination options. There are examples of practical use of evolutionary and genetic algorithms. Optimization of distribution routes using PHP&MySQL and Google Maps API technologies.
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Genetic Algorithm Design for Distribution Network Outfits Optimalization
Ondruš, Tomáš ; Skala, Petr (referee) ; Paar, Martin (advisor)
The work deals with genetic algorithms and their potential use in application software to optimize high voltage switching elements of distribution network. Theoretical part explains the basic concepts of genetic algorithms such as a gene, population and chromosome and basic principles of the development of genetic algorithms.. The main task of the thesis is to design the algorithm that will simulate the distribution of the sectionalizers by telecontrolled section switches or reclosers and analyze how to set the the parameters affecting the convergence speed of genetic algorithm. The basic parameters affecting the convergence of breeding, mutation probability, population size or using of elitism. The second goal is finding a suitable set of input parameters for the selected population sizes without and with using elitism. The results of the work determine the most appropriate settings for each generation and determining the approximate number of generations needed to find the best solution. The genetic algorithm applocation was tested on a less extensive distribution network with six switching elements
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Variabilita polymorfizmu v genu FABP3 a jeho asociace s ukazateli kvality masa u prasat
Boleslavová, Štěpánka
The aim of the study was to study the variability of the gene in the population FABP3 pig breed Czech large white. Analyze their association with indicators of pork production. Gene FABP3 belonging to multigene families FABP (fatty acid binding proteins affecting the transport of long chain fatty acids). Analyzed polymorphism was at position X98558:g.1321G>C in the 5'UTR region. The relative frequencies of genotypes were: HH = 0,87, Hh = 0,13. hh genotype was not detected in the monitored individuals. The values of the relative frequencies of alleles were as follows: H = 0,93 h = 0,07. Based on the association analysis showed a statistically significant difference between genotypes for stearic acid and linoleic acid. Highly statistically significant difference was observed with palmitic acid.
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