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The Overlooked Fact: the Critical Role of Bioinformatics Pipeline in Microbiome Analysis
Polakovičová, Petra
The research on the human microbiome has gained significant popularity over the past couple of years across both scientific and public communities. This area has revealed considerable knowledge, mainly thanks to next-generation sequencing. Even though technology possibilities evolve faster than ever, and there is an enormous amount of publicly available data, there are not yet precise procedures, methods, and bioinformatics tools to work accurately enough with microbiome data, and there are no standardized recommendations for bioinformatics pipelines to assess the most accurate results. Here, we demonstrate the potential inaccuracies that can arise from various bioinformatics processing of amplicon 16S RNA sequencing data by performing a comparative analysis of diverse pipeline configurations using mock community samples and biological material originating from biopsy samples obtained during regular colonoscopy from patients with primary sclerosing cholangitis.
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Functional annotation of non-model bacteria based on sequential homology
Polakovičová, Petra ; Musilová, Jana (oponent) ; Sedlář, Karel (vedoucí práce)
The genome sequence is an essential informational resource in the field of biology and it is, therefore, a constant subject of scientific research. Bioinformatics offers computational methods for genome’s automatic analysis and processing. The bachelor thesis is dedicated to the bacterial genome, its organization, and fundamental characteristics, and subsequently description of its annotation. It mainly focuses on functional annotation (description of the biological function of predicted genes) using assignment to clusters of orthologous genes (COG) based on sequential homology. It describes the most commonly used tools and databases that use this type of annotation and then compares some of them by annotating seven bacterial genomes. Its main task is to propose a new method that improves COG annotation and makes it easy to visualize.
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The COG-or: the Improved Functional Annotation of Bacterial Genomes
Polakovičová, Petra ; Sedlář, Karel
The study of bacterial organisms is given great emphasis in scientific research. By studying the bacterial genome, scientists can gain knowledge of various infectious diseases. Nowadays, it is even possible to edit genes and thus advancing the field of tailored medicine by treating many genetic diseases. Furthermore, it is becoming the norm to utilize bacteria in the industry for their ability to produce important products such as plastics, or fuels. It is therefore essential to extract the necessary information about its genes and other features. This paper focuses mainly on improving the functional annotation of bacterial genomes, classification of protein-coding sequences into clusters of orthologous groups, and visualization of the final annotated genome. For this task, the python package was developed with several functions for working with the outputs of multiple annotation tools, namely eggNOG-mapper, Operon-mapper, and Batch CD-Search. The package was tested on Clostridium diolis DSM 15410 and Clostridium beijerinckii DSM 791.
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Functional annotation of non-model bacteria based on sequential homology
Polakovičová, Petra ; Musilová, Jana (oponent) ; Sedlář, Karel (vedoucí práce)
The genome sequence is an essential informational resource in the field of biology and it is, therefore, a constant subject of scientific research. Bioinformatics offers computational methods for genome’s automatic analysis and processing. The bachelor thesis is dedicated to the bacterial genome, its organization, and fundamental characteristics, and subsequently description of its annotation. It mainly focuses on functional annotation (description of the biological function of predicted genes) using assignment to clusters of orthologous genes (COG) based on sequential homology. It describes the most commonly used tools and databases that use this type of annotation and then compares some of them by annotating seven bacterial genomes. Its main task is to propose a new method that improves COG annotation and makes it easy to visualize.
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