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CNV detection in bacterial genomes
Lacinová, Michaela ; Sedlář, Karel (referee) ; Škutková, Helena (advisor)
This master thesis deals with analysis of structural variation of genome and with methods of its sequencing across all generations. Subsequently it contains a description of copy number variation and methods of its detection. The experimental part focuses on algorithm proposal for CNV detection according analysis and testing of uneven coverage in genome, variable representation of GC content and distance of sequence reads. Finally, the algorithm for detecting copy number variation is tested on genomic data of bacteria Klebsiella pneumoniae.
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Evaluation of Organisms Relationship by Genomic Signal Processing
Škutková, Helena ; Tkacz, Ewaryst (referee) ; Schwarz,, Daniel (referee) ; Provazník, Ivo (advisor)
This dissertation deals with alternative techniques for analysis of genetic information of organisms. The theoretical part presents two different approaches for evaluation of relationship between organisms based on mutual similarity of genetic information contained in their DNA sequences. The first approach is currently standardized phylogenetics analysis of character based records of DNA sequences. Although this approach is computationally expensive due to the need of multiple sequence alignment, it allows evaluation of global and local similarity of DNA sequences. The second approach is represented by techniques for classification of DNA sequences in a form of numerical vectors representing characteristic features of their genetic information. These methods known as „alignment free“ allow fast evaluation of global similarity but cannot evaluate local changes. The new method presented in this dissertation combines the advantages of both approaches. It utilizes numerical representation similar to 1D digital signal, i.e. representation that contains specific trend along x-axis. The experimental part of dissertation deals with design of a set of appropriate tools for genomic signal processing to allow evaluation mutual similarity of taxonomically specific trends. On the basis of the mutual similarity of genomic signals, the classification in the form of dendrogram is applied. It corresponds to phylogenetic trees used in standard phylogenetics.
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Numerical methods for classification of metagenomic data
Vaněčková, Tereza ; Sedlář, Karel (referee) ; Škutková, Helena (advisor)
This thesis deals with metagenomics and numerical methods for classification of metagenomic data. Review of alignment-free methods based on nucleotide word frequency is provided as they appear to be effective for processing of metagenomic sequence reads produced by next-generation sequencing technologies. To evaluate these methods, selected features based on k-mer analysis were tested on simulated dataset of metagenomic sequence reads. Then the data in original data space were enrolled for hierarchical clustering and PCA processed data were clustered by K-means algorithm. Analysis was performed for different lengths of nucleotide words and evaluated in terms of classification accuracy.
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Automatic genotyping of bacteria by rep-PCR
Pelikánová, Veronika ; Maděránková, Denisa (referee) ; Škutková, Helena (advisor)
This thesis deals with automatic bacteria genotyping by rep-PCR method. Its theoretical part presents various methods of DNA typing, basic information on electrophoresis and modern electrophoretic approaches, including their problems, misleading data distortion. In order to automate typing, there has been introduced a program for phylogenetic sample classification from rep-PCR, also applicable for data from chip capillary electrophoresis. The program consists of three main parts: digitization, bandmatching and clustering apparatus to bacterial type classification. The result of the algorithm is a phylogenetic tree, which indicates the cluster of sapmles according to bacterial type. The program has a graphical user interface for possible use in the Children's Hospital. Finally, the program is tested with data from the Children´s Hospital.
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Analysis of animal mitochondrial genes for DNA barcoding
Brabencová, Klára ; Škutková, Helena (referee) ; Maděránková, Denisa (advisor)
The aim of this work is a literature review on the topic of the mitochondrial genome and DNA barcoding, building a dataset of mitochondrial sequences from GenBank database and creatione of a software function for extraction of individual genes that are present in the mitochondrial genome. This function was developed in Matlab. DNA barcoding is a method that uses short DNA sequence of mitochondrial genome for identification of species. There is no comprehensive work examining the appropriateness of different mitochondrial genes. This aim investigates the potential of other mitochondrial genes and evaluate their effectiveness for DNA barcoding and calculation of intra-and interspecific variability.
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Methods for fast sequence comparison and identification in metagenomic data
Kupková, Kristýna ; Škutková, Helena (referee) ; Sedlář, Karel (advisor)
Předmětem této práce je vytvoření metody sloužící k identifikaci organismů z metagenomických dat. Doposud k tomuto účelu spolehlivě dostačovaly metody založené na zarovnání sekvencí s referenční databází. Množství dat ovšem s rozvojem sekvenačních technik rapidně roste a tyto metody se tak stávají díky své výpočetní náročnosti nevhodnými. V této diplomové práci je popsán postup nové techniky, která umožňuje klasifikaci metagenomických dat bez nutnosti zarovnání. Metoda spočívá v převedení sekvenovaných úseků na genomické signály ve formě fázových reprezentací, ze kterých jsou následně extrahovány vektory příznaků. Těmito příznaky jsou tři Hjorthovy deskriptory. Ty jsou dále vystaveny metodě maximalizace věrohodnosti směsi Gaussovských rozložení, která umožňuje spolehlivé roztřídění fragmentů podle jejich příslušnosti k organismu.
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Digital image analysis of mitotic chromosomes
Danielová, Tereza ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
This master’s thesis is focused on digital image analysis of mitotic chromosomes. It deals with the design of the processing of digital images - from image preprocessing to clasification of each chromosomes, including testing on a set of images. This work introduces used cytogenetic methods, that are used to visualize chromosomes. In its practical part describes morphology operations and clasification procedure. Classification of the chomosomes was divided into 5 groups (A-G). All algorithms were created in the MATLAB program.
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