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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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Pupil with disorder of learning in primary school
Šustrová, Eliška ; Linková, Marie (advisor) ; Křivánek, Zdeněk (referee)
This thesis deals with specific learning disabilities on the first level of primary education. The theoretical part is devoted to the definition of the basic concepts, to the etiology of the occurrence of specific learning disabilities and to the classification of their manifestation. It draws up the possibilities of the diagnostics and of the follow-up re-education. It describes the possibilities of educating students with disabilities at basic schools or individually. The practical part of this thesis focuses on exploring the issue of specific learning disabilities on the first level of primary education, namely, in the third and fourth grade. Three case reports whose results most visibly pointed to a problem are also present here.
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Long-term memory detection with bootstrapping techniques: empirical analysis
Albert, Branislav ; Krištoufek, Ladislav (advisor) ; Avdulaj, Krenar (referee)
A time series has long range dependence if its autocorrelation function is not absolutely convergent. Presence of long memory in a time series has important consequences for consistency of several time series estimators and forecasting. We present a self-contained theoretical treatment of time series models necessary for study of long range dependence and survey a large list of parametric and semiparametric estimators of long range dependence. In a Monte Carlo study, we compare size and power properties of four estimators, namely R/S, DFA, GPH and Wavelet based method, when relying on asymptotic normality of the estimators and distributions obtained from the moving block bootstrap. We find out that the moving block bootstrap can improve the size of the R/S estimator. In general however, the moving block bootstrap did not perform satisfactorily for other estimators. GPH and Wavelet estimators offer the most reliable asymptotic confidence intervals.
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Differences in physiology between r and K bacterial strategists.
Moserová, Andrea ; Konopásek, Ivo (advisor) ; Krištůfek, Václav (referee)
Differences in physiology between r and K-bacterial strategists. The definition of bacterial r/K-strategists is currently based on the time interval they need to form a colony on agar plate. Also, their growth rate which is often used to identify r/K-position within a pair of bacterial strains. To date it was evidenced that also other physiological characteristics relate to bacterial r/K-status, for example their different ability to 1) adapt for changing conditions 2) utilize complex or very diluted substrates, 3) use secondary metabolites to cope with other strains and possibly also others. The intersection of macro- and microbiological r/K-conceptions lies in time distribution of r/K-strategists during succession. The aim of this study was to verify the basic r/K-characteristics on nine chosen strains and to correlate them with their physiological differences that are implicitly regarded as characteristic for r/K-groups. The study deals with growth rates measurements on both liquid and solid media, identification of fatty acid composition and membrane fluidity of strains cultivated at near-optimum and cold temperature in order to track the differences in cold adaptation. The study also deals with the description of possible new K-strategist characteristic: the lack of correlation between the colony...
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Gradient Boosting Machine and Artificial Neural Networks in R and H2O
Sabo, Juraj ; Bašta, Milan (advisor) ; Plašil, Miroslav (referee)
Artificial neural networks are fascinating machine learning algorithms. They used to be considered unreliable and computationally very expensive. Now it is known that modern neural networks can be quite useful, but their computational expensiveness unfortunately remains. Statistical boosting is considered to be one of the most important machine learning ideas. It is based on an ensemble of weak models that together create a powerful learning system. The goal of this thesis is the comparison of these machine learning models on three use cases. The first use case deals with modeling the probability of burglary in the city of Chicago. The second use case is the typical example of customer churn prediction in telecommunication industry and the last use case is related to the problematic of the computer vision. The second goal of this thesis is to introduce an open-source machine learning platform called H2O. It includes, among other things, an interface for R and it is designed to run in standalone mode or on Hadoop. The thesis also includes the introduction into an open-source software library Apache Hadoop that allows for distributed processing of big data. Concretely into its open-source distribution Hortonworks Data Platform.
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Manipulation of hydrological data in R
Ficaj, Václav ; Hanel, Martin (advisor) ; Stanislav, Stanislav (referee)
This thesis deals with the creation package in R language. This package should facilitate the work of European river basins. It should serve to derive the river basins in Europe. Package can be also used for extract value from the database of daily precipitation and temperature E-OBS for these derived river basins. This package is designed to work with standardized data. The basis of this package is to work with a Europe-wide database of rivers and catchment. This work also contain description of the all organisations, which has developed used data. There is also discusses the basic rules of production packages.
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Individual work with a child by logopedic prevention with focus on sounds L and R from the perspective of logopedic prevention officer
KRAUSOVÁ, Daniela
The aim of this bachelor thesis is to create a program of logopaedic prevention for individual work with a child as a general rule aged between five and six in kindergarten and with focus on sound L and R, which belong to the frequent speech impediment in pronunciation. In a theoretical part is described the general definition of logopaedics (speech therapy), its sense and there are given reasons of need for logopaedic prevention in kindergarten. The theoretical part is also focused on the development of speech and pronunciation of child at preschool age, on the articulation disorder and the diagnostics of pronunciation of child at preschool age. There are described the sorting of sounds of Czech language and the characteristic of sounds L and R. In practical part are described breathing, vocal, hearing, graphomotoric training and gymnastic of speech organs for development of articulatory organs and exercises for support of right pronunciation of sound L a R. In this part are also located pictures that illustrate and introduce the work with children.
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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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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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