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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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The Study of Management Business Development in Trade Organization
Matula, Jan ; Ing. Jan Pagáč. (referee) ; Jurová, Marie (advisor)
This Bachelor thesis focuses on the preparation of the proposal for the company Auto Jonáš s.r.o. which aims to streamline service management across the enterprise for greather customer satisfacrion. There is a destription of a possible solution from a theoretical point of view, where knowledge is captured from the literature on this topic. Another part of the work are used theoretical knowledge to a selected enterprice.
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Segmentation of cartilage tissue of mouse embryos in 3D micro CT data
Matula, Jan ; Vičar, Tomáš (referee) ; Chmelík, Jiří (advisor)
Manual segmentation of cartilage tissue in micro CT images of mouse embryos is a very time consuming process and significantly increases the time required for the research of mammal facial structure development. This problem might be solved by using a fully-automatic segmentation algorithm. In this diploma thesis a fully-automatic segmentation method is proposed using a convolutional neural network trained on manually segmented data. The architecture of the proposed convolutional network is based on the U-Net architecture with it's encoding part substituted for the encoding part of the VGG16 classification convolutional neural network pretrained on the ImageNet database of labeled images. The proposed network achieves Dice coefficient 0.8731 ± 0.0326 in comparison to manually segmented images.
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MHC And KIR Genotyping Of Macaques In HIV Infection Research
Matula, Jan
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, in demonstrated using genotyping of genes for MHC and KIR receptors of HIV positive macaques.
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Segmentation Of Cartilage Tissue In Micro Ct Images Of Mouse Embryos With Modified U-Net Convolutional Neural Network
Matula, Jan
Manual segmentation of cartilage tissue in micro CT images of mouse embryos is a very time-consuming process and significantly increases the time required for the research of mammal facial structure development. It is possible to solve this problem by using a fully-automatic segmentation algorithm. In this paper, a fully-automatic segmentation method is proposed using a convolutional neural network trained on manually segmented data. The architecture of the proposed convolutional network is based on the U-Net architecture with its encoding part substituted for the encoding part of the VGG16 classification convolutional neural network pre-trained on the ImageNet database of labelled images. The proposed network achieves average Dice coefficient 0.88 in comparison to manually segmented images.
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Segmentation of cartilage tissue of mouse embryos in 3D micro CT data
Matula, Jan ; Vičar, Tomáš (referee) ; Chmelík, Jiří (advisor)
Manual segmentation of cartilage tissue in micro CT images of mouse embryos is a very time consuming process and significantly increases the time required for the research of mammal facial structure development. This problem might be solved by using a fully-automatic segmentation algorithm. In this diploma thesis a fully-automatic segmentation method is proposed using a convolutional neural network trained on manually segmented data. The architecture of the proposed convolutional network is based on the U-Net architecture with it's encoding part substituted for the encoding part of the VGG16 classification convolutional neural network pretrained on the ImageNet database of labeled images. The proposed network achieves Dice coefficient 0.8731 ± 0.0326 in comparison to manually segmented images.
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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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The Study of Management Business Development in Trade Organization
Matula, Jan ; Ing. Jan Pagáč. (referee) ; Jurová, Marie (advisor)
This Bachelor thesis focuses on the preparation of the proposal for the company Auto Jonáš s.r.o. which aims to streamline service management across the enterprise for greather customer satisfacrion. There is a destription of a possible solution from a theoretical point of view, where knowledge is captured from the literature on this topic. Another part of the work are used theoretical knowledge to a selected enterprice.
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