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Analysis of Motion of People by a Stationary Camera
Smatana, Stanislav ; Juránková, Markéta (referee) ; Herout, Adam (advisor)
Hlavním cílem této práce bylo navrhnout a vytvořit systém sledování osob s aplikací v oboru bezpečnosti nebo pro analýzu chování zákazníka v obchodě. Systém byl úspěšně implementován pomocí metod KLT trekování, AdaBoost klasifikátoru a datové asociace pomocí Markovských řetězců a metody Monte Carlo. Implementace umožňuje analýzu pohybu lidí ve vnitřních i vnějších prostorech.
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Bioinformatic Tool for Classification of Bacteria into Taxonomic Categories Based on the Sequence of 16S rRNA Gene
Valešová, Nikola ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
Tato práce se zabývá problematikou automatizované klasifikace a rozpoznávání bakterií po získání jejich DNA procesem sekvenování. V rámci této práce je navržena a popsána nová metoda klasifikace založená na základě segmentu 16S rRNA. Představený princip je vytvořen podle stromové struktury taxonomických kategorií a používá známé algoritmy strojového učení pro klasifikaci bakterií do jedné ze tříd na nižší taxonomické úrovni. Součástí práce je dále implementace popsaného algoritmu a vyhodnocení jeho přesnosti predikce. Přesnost klasifikace různých typů klasifikátorů a jejich nastavení je prozkoumána a je určeno nastavení, které dosahuje nejlepších výsledků. Přesnost implementovaného algoritmu je také porovnána s několika existujícími metodami. Během validace dosáhla implementovaná aplikace KTC více než 45% přesnosti při predikci rodu na datových sadách BLAST 16S i BLAST V4. Na závěr je zmíněno i několik možností vylepšení a rozšíření stávající implementace algoritmu.
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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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Web Application for Primer Selection for 16S rRNA Amplicon Sequencing
Jurča, Jan ; Martínek, Tomáš (referee) ; Smatana, Stanislav (advisor)
Main goal of this thesis was an implementation of web application, that can evalutate and recommend primer pairs for 16S rRNA amplicon sequencing, according to users specific needs and by this simplify the procces of primer pair selection. Primer pair evaluation is based on database of primer pairs, which contains data about senzitivity and specifity of each primer pair. Part of the work was also the performance optimization of the primer pair analysis algorithm, that computes senzitivity and specifity data. This optimization helped in an integration of algorithm into the application, which means that users can submit their own primer pair sequences, run analysis and get informations about position of amplified region, sensitivity and specifity.
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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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Tool for Visualization of Microbiome Data
Mišáková, Silvia ; Martínek, Tomáš (referee) ; Smatana, Stanislav (advisor)
Táto práca sa zameriava na vytvorenie nového nástroja pre vizualizáciu mikrobiomových dát. Vytvorený nástroj používa pre redukciu dimenzií analýzu hlavných komponent (PCA) a analýzu hlavných súradníc (PCoA). V prípade výpočtu dištančnej matice sú použité metriky Bray-Curtis odlišnosť a UniFrac. Spracované dáta sú následne ofarbené na základe užívateľom zvolených metadát. Výsledky sú prezentované pomocou dvoch typov grafov. Prvý z nich je stĺpcový a zobrazuje podiel každej hlavnej zložky. Druhý, bodový graf, vizualizuje konečný výsledok požadovanej analýzy. V rámci práce bola pridaná možnosť stiahnuť si vypočítanú maticu a taktiež tabuľku prvých N hlavných zložiek vypočítaných danou analýzou.
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Bacteria Classification Based on Marker Genes
Pelantová, Lucie ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
The aim of this work is proposal of new method for bacteria classification based on sequences of marker genes. For this purpose was chosen 10 marker genes. Resulting MultiGene classifier processes data set by dividing it in several groups and choosing gene for each group which can distinguish this group with best results. This work describes implementation of MultiGene classifier and its results in comparison with other bacteria classifiers and with classification based entirely on gene 16S rRNA.
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Bacteria Classification into Taxonomic Categories Based on Properties of 16s rRNA
Grešová, Katarína ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
The main goal of this thesis was to design and implement a tool that would be able to classify the sequences of the 16S rRNA gene into taxonomic categories using the properties of the 16S rRNA gene. The created tool analyzes all input sequences simultaneously, which differs from common classification approaches, which classify input sequences individually. This tool relies on the fact that bacteria contain several copies of the 16S rRNA gene, which may differ in sequence. The main contribution of this work is design, implementation and evaluation of the capabilities of this tool. Experiments have shown that the proposed tool is able to identify the corresponding bacteria for smaller datasets and determine the correct ratios of their abundances. However, with larger datasets, the state space becomes very large and fragmented, which requires further improvements in order for it to search the state space in an efficient way.
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Search of Related Enzymes
Borko, Simeon ; Smatana, Stanislav (referee) ; Hon, Jiří (advisor)
Millions of new proteins discovered each year cannot be characterized by classical biochemical methods due to their demands of time and cost. Among the unexplored proteins, there may be enzymes useful in both industry and academy, mostly for ecological production of chemical compounds. The result of the thesis is a web application which, based on the input proteins, searches the database for similar proteins. The proteins are filtered using essential residues of the input proteins and marked as putative biocatalysts. Finally, the proteins are annotated so that the user can make an informed decision about which proteins to select for experimental laboratory verification. The developed tool facilitates multi-step analysis and recommends proteins for experimental verification of their enzymatic function. The web interface is freely available at https://loschmidt.chemi.muni.cz/enzymeminer/. The tool was published in the international journal Nucleic Acids Research.
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Bioinformatic Tool for Estimation of Abundances of Bacterial Functional Molecules in Biological Samples Based on 16S rRNA Metagenomic Data
Bieliková, Michaela ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
Ľudské telo je prostredím pre život neuveriteľného množstva mikróbov. Niektoré z nich môžu spôsobovať rôzne choroby, ale ďalšie, napríklad črevný mikrobióm, sú pre život a zdravie človeka nepostrádateľné. Nanešťastie, črevný mikrobióm nie je detailne preštudovaný, pretože obsahuje tisíce rôznych druhov baktérií, z ktorých väčšina sa nedá kultivovať v laboratórnych podmienkach. Riešením tohto problému sú nové rýchle metódy sekvenovania v kombináciou s bioinformatickými nástrojmi na výpočet funkčného profilu baktérií vo vzorke. V tejto práci si predstavíme existujúce nástroje predpovedajúce funkčný profil, a následne navrhneme nový nástroj, ktorý môže implementovať konsenzus nad výsledkami existujúcich nástrojov, alebo sa môže jednať o úplne nový nástroj.
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