|
|
Dynamic metabolomic prediction from genetic variation
Nemčeková, Petra ; Weckwerth, Wolfram (oponent) ; Schwarzerová, Jana (vedoucí práce)
Hordeum vulgare, like many other crops, suffers from the reduction of genetic diversity caused by climate changes. Therefore, it is necessary to improve the performance of its breeding. Nowadays, the area of interest in current research focuses on indirect selection methods based on computational prediction modeling. This thesis deals with dynamic metabolomic prediction based on genomic data consisting of 33,005 single nucleotide polymorphisms. Metabolomic data include 128 metabolites belonging to 25 Halle exotic barley families. The main goal of this thesis is to create dynamic metabolomic predictions using different approaches chosen from relevant publications. The created models can be helpful for the prediction of phenotype or for revealing important traits of Hordeum vulgare.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
Gene regulation in Clostridium beijerinckii NRRL B-598
Schwarzerová, Jana ; Jurečková, Kateřina (oponent) ; Sedlář, Karel (vedoucí práce)
The master’s thesis deals with the study of gene regulatory in Clostridium beijerinckii NRRL B-598 for inference gene regulatory network for C. beijerinckii NRRL B-598. The theoretic part describes basic nomenclature gene regulatory with the main focus on gene regulatory networks nomenclature. Laboratory methods which serve to obtain suitable gene describing express data are described there. These data are based on the study of gene regulatory and inference gene regulatory networks. The thesis is mainly focused on the RNA-Seq technology and brief description of laboratory data which were gathered using the strain C. beijerinckii NRRL B-598. In the practical part of the thesis pre-processing of these raw laboratory data and following gene regulatory research is performed which focuses on inference operons and creating first gene regulatory networks for C. beijerinckii NRRL B-598 using different approaches.
|
|
|
Segmentace ultrazvukových sekvencí
Schwarzerová, Jana ; Odstrčilík, Jan (oponent) ; Mézl, Martin (vedoucí práce)
Tato bakalářská práce se zabývá základním popisem ultrasonografie, principem kontrastního zobrazení a aplikací segmentačních metod v ultrasonografické problematice. Z uvedených segmentačních metod byly některé metody vybrány a implementovány v programu Matlab verze R2015b. Algoritmy byly testovány na uměle vytvořených datech, na ultrazvukových fantómech i na reálných ultrazvukových obrázcích. Následně byla práce rozšířena na segmentaci ultrazvukových sekvencí.
|
host ::
RSS.