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Dynamic metabolomic prediction from genetic variation
Nemčeková, Petra ; Weckwerth, Wolfram (referee) ; Schwarzerová, Jana (advisor)
Hordeum vulgare, tak ako mnoho ďalších plodín, trpí redukovaním genetickej rôznorodosti spôsobeným klimatickými zmenami. Preto je potrebné zlepšiť účinnosť jeho kríženia. Oblasť záujmu sa v poslednej dobe obracia na výskum nepriamych selekčných metód založených na výpočetných predikčných modeloch. Táto práca sa zaoberá dynamickou metabolomickou predikciou založenou na genomických dátach, ktoré pozostávajú z 33,005 jednonukleotidových polymorfizmov. Metabolomické dáta zahŕňajú 128 metabolitov 25 rodín Halle exotického jačmeňa. Hlavným cieľom tejto práce je vytvoriť metabolomické predikcie dynamických dát pomocou rôznych metód, ktoré boli vybrané na základe rôznych publikácií. Vytvorené modely napomôžu predikcii fenotypu alebo odhaleniu dôležitých vlastností rastliny Hordeum vulgare.
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Metabolite Genome-Wide Association Studies Of Arabidopsis Thaliana
Schwarzerová, Jana
Current research based on the edge of bioinformatics and ecology engineering has hugepotential due to combination of laboratory analyses and advanced bioinformatics algorithms.The paper deals with a combination of GC-MS and LC-MS based metabolomic analysis for identificationand quantitation of metabolites in environmental perturbations with advanced bioinformaticsapproach of metabolite genome-wide association studies (mGWAS). This complex view is appliedto Arabidopsis thaliana. The main goal is to obtain genetic predictions focused on A. thalianaunder different environmental conditions. Currently, important ecological issues such as climatechange, pollution etc. have impact on the change of environment. It has a great effect on plantswhich serves as producers of oxygen or food. While simple observation reveals only a phenotypechange, changes in genotypes of organisms can be captured using mGWAS and further utilized inindustrial ecology and biotechnology.
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Operon-Expresser: The Innovated Gene Expression-Based Algorithm For Operon Structures In-Ference
Schwarzerová, Jana
Current biotechnological research of bacterial genomes has huge potential due to the useof next-generation sequencing (NGS) platforms. NGS era opens paths for analysis of data for sufficientdescription of microorganisms with ecology and biotechnology potential in the future. Althoughsome tools for inference of specific structures in bacterial genomes exist, their pipelines andmethodologies are often based only on searching bacterial genome databases and comparison withmodel microorganisms. This paper deals with the design of a new algorithm for operon structuresinference in bacterial genomes. The algorithm combines searching in bacterial databases and geneexpression information processing. The algorithm was implemented in R language and tested onClostridium beijerinckii NRRL B-598. The bacterium is a typical performer in the field of biofuelsproduction due to its ability to produce butanol. Thanks to that this bacterial organism can be ofgreat potential from an ecological and biotechnological point of view. The paper also provides acomparison of operon structures derived by Operon-mapper and its extending by Operon-expresser.
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Reproducible Analytical Pipeline For Using Raw Rna-Seq Data From Non-Model Organisms
Schwarzerová, Jana
Current biotechnological research of bacterial or archaeal genomes has huge potential due to the use of the next generation sequencing (NGS) platforms. NGS era unravelled huge analysis data for sufficiency description microorganisms with ecology potential in future. Nowadays, efforts lie in creating comprehensive pipelines that can be used for pre-processing analysis to enable effective following steps of high throughput data processing. This paper deals with design of data analysis pipeline for using raw RNA-Seq data that was applied to the Clostridium beijerinckii NRRL B-598. The bacterium is typical performer in the field of biofuels production thanks to its ability to produce butanol. Unfortunately, it is non-model organism as many other microorganisms which can be of great potential from ecological point of view. The proposed pipeline offers to take necessary steps in initial data processing that produces data of comparable quality to widely studied model organisms. Therefore, it can be combined with following pipelines for gene regulatory network inference, which was up to date matter of non-model organisms.
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Gene regulation in Clostridium beijerinckii NRRL B-598
Schwarzerová, Jana ; Jurečková, Kateřina (referee) ; Sedlář, Karel (advisor)
Diplomová práce se zabývá studiem genové regulace v Clostridium beijerinckii NRRL B-598, pro následné odvození genové regulační sítě bakterie C. beijerinckii NRRL B-598. V teoretické části této práce je uvedena obecná nomenklatura problematiky genové regulace se zaměřením na nomenklaturu genových regulačních sítí. Následně jsou zde popsané laboratorní metody, sloužící pro získání vhodných dat popisující expresi genů. Tato data jsou základem pro studium genové regulace a návrhy genových regulačních sítí. Práce se zaměřuje především na technologii RNA-Seq a stručný popis laboratorních dat získaných ze zmíněné bakterie C. beijerinckii NRRL B-598. V praktické části se práce zabývá předzpracováním těchto surových laboratorních dat a následným studiem genové regulace se zaměřením na odvození operonů a vytvoření prvních genových regulačních sítí pomocí různých přístupů pro C. beijerinckii NRRL B-598.
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Image segmentation of ultrasound images
Schwarzerová, Jana ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This bachelor’s thesis deals with basic description of ultrasonography, principles of contrast-enhanced imaging and application of segmentation methods in ultrasound problematics. Some individual methods were implemented in Matlab, version R2015b. Algorithms were tested on synthetic images data, on ultrasound phantom images data and on real ultrasound images. Then the thesis was extended by ultrasound sequences segmentation.
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