National Repository of Grey Literature 29 records found  previous11 - 20next  jump to record: Search took 0.01 seconds. 
Methods for gene prediction in prokaryotic genomes
Nykrýnová, Markéta ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
This bachelor thesis deals with methods of gene prediction in prokaryotic genomes. First part of the thesis introduces prokaryotic cell, its genome, expression of genetic information and methods for gene prediction. Following part describes three software products for gene prediction. Chosen software was tested against specific genome and next chapter presents obtained results. The last part describes program called Gene_finder and its results.
Genotyping of Klebsiella pneumoniae isolates
Nykrýnová, Markéta ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
This master thesis deals with typing of Klebsiella pneumoniae isolates. The first part of the thesis introduces molecular typing methods. Then bacterial genomes and Klebsiella pneumoniae are characterized. Following part describes data validation, assembly of genomes and proposed algorithm for finding genes with high variability. In last part obtained results are presented and validated on other genomes of Klebsiella pneumoniae.
Gene identification in nanopore squiggles
Talanin, Nikita ; Nykrýnová, Markéta (referee) ; Bartoň, Vojtěch (advisor)
Nanopore sequencing is a new and rapidly developing technology that allows for the direct sequencing of single-stranded DNA and RNA in real-time. The result of the sequencing is the so-called squiggle, which is a time series of current intensities as nucleotides pass through the nanopore. Identifying genes in these squiggles is a crucial step for the utilization of this data in genomic studies. This bachelor's thesis focuses on the development and testing of a method for automatic gene identification in squiggles from nanopore sequencing. The aim was to create a system capable of quickly and accurately identifying genes in squiggles, thereby supporting further analysis and interpretation of nanopore sequencing data. The method utilizes Convolutional Neural Networks (CNN), which have been successfully used in many other areas of bioinformatics. A large dataset of squiggles, labeled according to the gene they represent, was used to train the model. The results show that the system can identify genes in squiggles with a certain level of accuracy and can be an effective tool for nanopore sequencing data analysis
Antibiotic resistance profile determination in hybrid assembled bacterial genomes
Dzurčaninová, Natália ; Škutková, Helena (referee) ; Nykrýnová, Markéta (advisor)
Antibiotická rezistencia je vážny problém vo väčšine spôsobený zmenami v bakteriálnom genóme. Získavanie a uchovávanie spoľahlivých bakteriálnych genomických dát je preto nevyhnutné pre štúdium mechanizmov a prenosu antibiotickej rezistencie. Táto práca popisuje bakteriálny genóm, antibiotickú rezistenciu a nástroje pre jej identifikáciu spolu s procesmi nevyhnutnými pre zisk genómov, sekvenáciu a skladanie. Sústreďuje sa na hybridné skladanie genómov spravidla vysoko rezistentných baktérií Klebsiella pneumoniae a ich nasledujúcich analýz. Cieľom týchto analýz je skonštruovať profily antibiotických rezistencií a určiť fylogenetickú príbuznosť genómov.
Gene identification in nanopore squiggles
Talanin, Nikita ; Nykrýnová, Markéta (referee) ; Bartoň, Vojtěch (advisor)
Nanopore sequencing is a new and rapidly developing technology that allows for the direct sequencing of single-stranded DNA and RNA in real-time. The result of the sequencing is the so-called squiggle, which is a time series of current intensities as nucleotides pass through the nanopore. Identifying genes in these squiggles is a crucial step for the utilization of this data in genomic studies. This bachelor's thesis focuses on the development and testing of a method for automatic gene identification in squiggles from nanopore sequencing. The aim was to create a system capable of quickly and accurately identifying genes in squiggles, thereby supporting further analysis and interpretation of nanopore sequencing data. The method utilizes Convolutional Neural Networks (CNN), which have been successfully used in many other areas of bioinformatics. A large dataset of squiggles, labeled according to the gene they represent, was used to train the model. The results show that the system can identify genes in squiggles with a certain level of accuracy and can be an effective tool for nanopore sequencing data analysis
Antibiotic resistance profile determination in hybrid assembled bacterial genomes
Dzurčaninová, Natália ; Škutková, Helena (referee) ; Nykrýnová, Markéta (advisor)
Antibiotická rezistencia je vážny problém vo väčšine spôsobený zmenami v bakteriálnom genóme. Získavanie a uchovávanie spoľahlivých bakteriálnych genomických dát je preto nevyhnutné pre štúdium mechanizmov a prenosu antibiotickej rezistencie. Táto práca popisuje bakteriálny genóm, antibiotickú rezistenciu a nástroje pre jej identifikáciu spolu s procesmi nevyhnutnými pre zisk genómov, sekvenáciu a skladanie. Sústreďuje sa na hybridné skladanie genómov spravidla vysoko rezistentných baktérií Klebsiella pneumoniae a ich nasledujúcich analýz. Cieľom týchto analýz je skonštruovať profily antibiotických rezistencií a určiť fylogenetickú príbuznosť genómov.
Advanced Computational Methods for Increasing the Discriminatory Power of Genotyping Methods
Nykrýnová, Markéta ; Budinská, Eva (referee) ; Hrabák,, Jaroslav (referee) ; Škutková, Helena (advisor)
Tato disertační práce je zaměřena na vytvoření nových výpočetních metod, které zvýší diskriminačních schopnost genotypizačních metod. Hlavní důraz je kladen na odlišení blízce příbuzných bakterií, které pocházejí například z jedné nemocnice či jednoho oddělení. V první části práce jsou popsány současné typizační metody a jsou představeny nové postupy pro identifikaci genetických markerů s vysokou mírou sekvenční variability, pomocí kterých lze lépe rozlišit bakteriální populaci. Navržené metody jsou založeny na výpočtu signálů entropie a analýze nenamapovaných čtení. Druhá část práce se zabývá návrhem nových metod zpracování surových dat z nanopórového sekvenování, které lze použít pro rychlou vysoce citlivou typizaci bakterií bez nutnosti převádět proudové signály na nukleotidové sekvence. Předložená práce přispívá ke zlepšení a zpřesnění rutinně používaných typizačních metod pomocí navržených bioinformatických postupů a představuje unikátní přístup využití doposud experimentální techniky nanopórového sekvenování pro rychlou genotypizaci a analýzu bakterií.
Processing and analysis of the human gut microbiome from 16S rDNA sequencing data
Zbudilová, Michaela ; Jurečková, Kateřina (referee) ; Nykrýnová, Markéta (advisor)
This bachelor´s thesis deals with the analysis of the human intestinal microbiome from 16S rRNA data. In the first part, the intestinal microbiome is theoretically described, and then the methods of its processing and evaluation using analysis of taxonomic categories and sample diversity are mentioned. The second part focuses on the data processed in the thesis and the format in which those data are provided. In the third part, the proposed algorithm used to process the data is described, and the results obtained by running this algorithm are evaluated. In the fourth part of the thesis, the samples from the University Hospital Brno are processed using the proposed algorithm. The last part of the thesis focuses on the script, which is used to generate the reports which can be used for diagnostic purposes in the University Hospital Brno.
Processing and analysis of the human lung microbiome from nanopore sequencing data
Molíková, Anna ; Bartoň, Vojtěch (referee) ; Nykrýnová, Markéta (advisor)
This bachelor’s thesis deals with processing and analysis of the human lung microbiome from nanopore sequencing data. Firstly this thesis introduces the lung microbiome and its composition in health and illness. Then it focuses on generations of sequencing technologies, mainly describing nanopore sequencing. The last chapter discusses different methods used for lung microbiome analysis. The practical part of this thesis preprocesses sequencing data, followed by their taxonomic analysis and the search for antibiotic resistance genes. From the obtained results, the composition of the lung microbiome in each of the processed samples is then evaluated.
Comparative and phylogenetic analysis of viruses in the University Hospital Brno
Švestková, Tereza ; Sedlář, Karel (referee) ; Nykrýnová, Markéta (advisor)
This thesis is focused on the SARs-CoV-2 coronavirus associated with severe acute respiratory syndrome, which was first identified in 2019. This coronavirus caused a pandemic that affected almost the entire world. Knowledge of the genetic information is needed for vaccine development, to determine infectivity and to predict the evolution of SARs-CoV-2 variants. To obtain genetic information, RNA must be sequenced and these genomic sequences must be assembled. By comparing the assembled genomes, it is possible to find out which part of the organism has mutated. Phylogenetic analysis is performed on the basis of the concordance or divergence in the assembled genomes, which indicates the evolution of the organism and shows the evolutionary relationship with other organisms. The practical part is focused on the assembly of genomes from samples from patients in the University Hospital Brno and evaluation of the quality of the assembly. After the genomes are assembled, the next goal is to evaluate the variability and subsequent phylogenetic analysis.

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