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Effect of emotive stimulation in EEG signal
Vaněčková, Tereza ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with emotions and their effect on EEG signal. Firstly, method of electroencephalography, the method of scanning EEG signal, its properties, frequency bands and signal affecting factors are described. The following is an explanation of emotions, its expression, theories of emotion origin, dimensions, classification and lateralization of emotional experience. Furthermore, review of studies that have influenced this work is provided. The practical part consists of the experimental measurement description, principle of stimuli selection, signal EEG recording using the Emotiv EPOC device and the Self-Assessment Manikin evaluation. There are also clarified methods of data processing and selection of emotion related features of EEG signal. The final section summarizes the achieved results and outlines possible continuation of emotional states recognizing.
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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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Luminiscenční nanočástice pro bioanalytické aplikace =: Luminescent nanoparticles for bioanalytical applications /
Vaněčková, Tereza
The dissertation thesis entitled Luminescence nanoparticles for bioanalytical applications deals with the use of optical nanomaterials in life sciences. An overview of the commonly used luminescent nanoprobes is provided together with their advantages over commonly used organic dyes or fluorescence proteins. Next, surface modifications and biofunctionalization of nanoparticles with targeting moieties are discussed. Molecularly imprinted polymers are introduced as an alternative surface modification enabling biorecognition. Finally, theoretical part is concluded with recent examples of the luminescent nanoparticles in bioanalytical and imaging applications. The scientific results of the Ph.D. candidate are presented in the form of 2 review articles and 3 research articles in the peer reviewed journals.
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Alignment-free Methods for Classification of Metagenomic Data
Vaněčková, Tereza
Metagenomics studies microbial communities by analyzing their genomic content directly sequenced from the environment. In this contribution, alignment-free methods based on word frequency will be introduced. It has been proven, that these methods are effective in processing of short metagenomic sequence reads produced by Next-Generation Sequencing technologies. To evaluate the potential of word frequency based methods, the k-mer analysis was applied on simulated dataset of metagenomic sequence reads with length of 600 nucleotides. Then the data were enrolled for a hierarchical cluster analysis. Results have shown that the proposed method is able to cluster genome fragments of the same taxa.
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Effect of emotive stimulation in EEG signal
Vaněčková, Tereza ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with emotions and their effect on EEG signal. Firstly, method of electroencephalography, the method of scanning EEG signal, its properties, frequency bands and signal affecting factors are described. The following is an explanation of emotions, its expression, theories of emotion origin, dimensions, classification and lateralization of emotional experience. Furthermore, review of studies that have influenced this work is provided. The practical part consists of the experimental measurement description, principle of stimuli selection, signal EEG recording using the Emotiv EPOC device and the Self-Assessment Manikin evaluation. There are also clarified methods of data processing and selection of emotion related features of EEG signal. The final section summarizes the achieved results and outlines possible continuation of emotional states recognizing.
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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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