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Tool for Classification of Lifestyle Traits Based on Metagenomic Data from the Large Intestine
Kubica, Jan ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
This thesis deals with analysis of human microbiome using metagenomic data from large intestine. The main focus is placed on bacteria composition in a sample on different taxonomic levels regarding the lifestyle traits of an individual. For this purpose, a tool for classification of several attributes was created. It considers attributes like diet type and eating habits (vegetarian, vegan, omnivore), gluten and lactose intolerance, body mass index, age or sex. From range of machine learning perspectives considering K Nearest Neighbours (kNN), Random Forest (RF) and Support Vector Machines (SVM) were used. Datasets for training and final evaluation of the classifier were taken from American Gut project. The thesis also focuses on particular problems with metagenomic datasets like its multidimensionality, sparsity, compositional character and class imbalance.
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Methods Of Processing Oxford Nanopore Sequencing
Data For Metagenomics
Barilíková, Lujza
The presented paper describes a new method of processing data produced by revolutionary sequencing technology introduced by Oxford Nanopore Technologies – MinION, which holds a great promise in the field of metagenomics. Low cost, produced long reads and portability, due to its small dimensions, represents only one of the many advantages of this technology. Despite of the benefits, there is a lack of available computational tools for handling the produced data and that is the reason, why a new method of processing such data should be created. In this study such method is created based on dimensionality reduction for data visualization.
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Methods for Comparative Analysis of Metagenomic Data
Sedlář, Karel ; Vinař,, Tomáš (referee) ; Lexa, Matej (referee) ; Provazník, Ivo (advisor)
Moderní výzkum v environmentální mikrobiologii využívá k popisu mikrobiálních komunit genomická data, především sekvenaci DNA. Oblast, která zkoumá veškerý genetický materiál přítomný v environmentálním vzorku, se nazývá metagenomika. Tato doktorská práce se zabývá metagenomikou z pohledu bioinformatiky, která je nenahraditelná při výpočetním zpracování dat. V teoretické části práce jsou popsány dva základní přístupy metagenomiky, včetně jejich základních principů a slabin. První přístup, založený na cíleném sekvenování, je dobře rozpracovanou oblastí s velkou řadou bioinformatických technik. Přesto mohou být metody pro porovnávání vzorků z několika prostředí podstatně vylepšeny. Přístup představený v této práci používá unikátní transformaci dat do podoby bipartitního grafu, kde je jedna partita tvořena taxony a druhá vzorky, případně různými prostředími. Takový graf plně reflektuje kvalitativní i kvantitativní složení analyzované mikrobiální sítě. Umožňuje masivní redukci dat pro jednoduché vizualizace bez negativních vlivů na automatickou detekci komunit, která dokáže odhalit shluky podobných vzorků a jejich typických mikrobů. Druhý přístup využívá sekvenace celého metagenomu. Tato strategie je novější a příslušející bioinformatické nástroje jsou méně propracované. Hlavní výzvou přitom zůstává rychlá klasifikace sekvencí, v metagenomice označovaná jako „binning“. Metoda představená v této práci využívá přístupu zpracování genomických signálů. Tato unikátní metodologie byla navržena na základě podrobné analýzy redundance genetické informace uložené v genomických signálech. Využívá transformace znakových sekvencí do několika variant fázových signálů. Navíc umožňuje přímé zpracování dat ze sekvenace nanopórem v podobě nativních proudových signálů.
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Signal Based Feature Selection for Fast Classification of Sequences in Metagenomics
Sedlář, Karel
The rapid development in DNA sequencing techniques brings completely new possibilities into metagenomics research. No longer is the whole metagenome sequencing an issue. On the other hand, this progress lies new demands on bioinformatics tools indented to process this kind of data. Unlike the amplicon based sequencing where every sequence represents a particular gene, the whole metagenome sequencing produce sequences that are random pieces of genomes in the metagenome. Therefore, the reference database for identification of these sequences cannot be used. Here, we present fast feature selection based on genomic signal processing for alignment-free classification of sequences in the metagenome.
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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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Methods of processing Oxford Nanopore sequencing data for metagenomics
Barilíková, Lujza ; Provazník, Ivo (referee) ; Kupková, Kristýna (advisor)
The revolutionary sequencing technology introduced by Oxford Nanopore Technologies – MinION holds a great promise in the field of metagenomics. Low cost, produced long reads and portability, due to its small dimensions, represents only one of the many advantages of this technology. Despite the benefits, there is a lack of available computational tools for handling the produced data. The theoretical part of the thesis first introduces current sequencing technologies with main focus on the third-generation sequencing and especially on nanopore sequencing. The recent possibilities of metagenomic data visualization are introduced. The main purpose of the bachelor thesis is to make an algorithm for binning of metagenomic samples based on use of dimensionality reduction techniques straight on raw data produced by nanopore sequencing.
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Detection of Enzymes in Metagenomic Data
Smatana, Stanislav ; Martínek, Tomáš (referee) ; Hon, Jiří (advisor)
This thesis presents specification and implementation of a system for detection of enzymes in metagenomic data. The detection is based on a provided enzyme sequence and its goal is to search the metagenomic sample for its novel variants. In order to guarantee that found enzymes truly have the desired catalytic function, the system employs a number of catalytic function verification methods. Their specification, implementation and evaluation is one of the main contributions of this thesis. Experiments have shown, that proposed methods reach sensitivity as high as 89%, specificity of 95%, values of AUC metric above 0.9 and average throughput of 1,203 verifications per second on regular personal computer. Evaluation of the system also led to discovery of a partial sequence of novel haloalkane dehalogenase enzyme in a metagenomic sample from soil. The implementation is able to work on a personal computer as well as on a grid computing environment.
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Microbial consortia and metagenome of industrially polluted soil: occurrence of genes encoding AEH
Pitkina, Anastasiya ; Kyslík, Pavel (advisor) ; Lichá, Irena (referee)
Soils contain highly diverse consortia of bacteria making them very attractive starting points for both culture-dependent and metagenomic discovery efforts. The present diploma thesis analyses the composition of the microbial community from pharmaceutically polluted soil, with the employment of next-generation Illumina sequencing of 16S rDNA region. This analysis revealed high complexity of the soil microbial environment and confirmed that anthropogenic activity (represented by production of beta- lactam antibiotics) influences the variability and abundance of the species, yet without reducing the microbial diversity. In the second part of the thesis, isolation and heterologous expression of a novel gene encoding alpha-amino acid ester hydrolase (AEH) from a cultivable soil microorganism B. cereus is described. AEHs possess industrial potential for biocatalytic synthesis of semi-synthetic beta-lactam antibiotics, which are presently of great clinical importance. Powered by TCPDF (www.tcpdf.org)
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The use of parallel sequencing methods in microbiology.
Pavlíková, Magdaléna ; Najmanová, Lucie (advisor) ; Vopálenský, Václav (referee)
The thesis describes the history of development of sequencing methods with special focus on the modern effective parallel sequencing methods and their application in microbiology. The development and improvements of sequencing systems lead to the acceleration of the process and considerable decrease of price, which consequently allow wider spectrum of applications. Each of the sequencing systems has its characteristic features including drawbacks stemming from the principle of the respective method. Not every method suitable for all the applications. In the thesis the sequencing methods are compared and examined with respect to their appropriateness for certain application fields in microbiology. The currently available sequencing methods are usually categorized into three "generations", distinguished by sets of typical features. First generation methods include the systems of Sanger and Maxam-Gilbert; "next generation" is represented by methods 454, Illumina, SOLiD and Helicos; and finally SMRT, Ion Torrent and the commercially not yet available nanopore sequencing are usually called "next-next generation". Now the sequencing becomes a standard technology of molecular biology, not only in the basic microbiological research, but it is also widely applied in medicine (quick identification of patogenes,...
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