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Web Application for Bioinformatics Education - Genetic Code
Kilián, Martin ; Martínek, Tomáš (referee) ; Burgetová, Ivana (advisor)
This thesis briefly describes basic informations in moleculary biology. Thesis deals with a transfer of information from DNA into RNA through uprotein, are also briefly described the methods and algorithms dealing with the detection of genome. The larger part deals with the recognition cue coded signals and determination of sequences and their subsequent transcription and translation, which demonstration program was needed to create. The final result is s web application as the education system.
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Clustering of Protein Sequences Based on Primary Structure of Proteins
Jurásek, Petr ; Stryka, Lukáš (referee) ; Burgetová, Ivana (advisor)
This master's thesis consider clustering of protein sequences based on primary structure of proteins. Studies the protein sequences from they primary structure. Describes methods for similarities in the amino acid sequences of proteins, cluster analysis and clustering algorithms. This thesis presents concept of distance function based on similarity of protein sequences and implements clustering algorithms ANGES, k-means, k-medoids in Python programming language.
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Techniques for Comparing Biological Sequences
Sladký, Roman ; Křivka, Zbyněk (referee) ; Burgetová, Ivana (advisor)
This work presents the building up of basic biological units DNA, RNA and proteins as well as their function. Provided data are kept in biological databases which are connected worldwide to supply preferable communication along with all kinds of available information to be used in the scientific research. The secret of alive is hidden in genes coded in sequences of nucleotides. Genes enable the creation of proteins which are made of sequences of amino-acids. The wide-spread methods of comparing these sequences are FASTA and BLAST algorithms. Their base is used for the PSProt program which is described in this work. PSProt program is the tool for comparing the sequences of proteins. First it is necessary to synthesise the protein from the DNA oligonucleotide because it codes the surveyed protein. The most similar proteins are searched out by heuristic of hitpoints, then their final score that is essential for aligning is modified by semiglobal alignment algorithm.
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The use of microcalorimetric methods in the study of the protective effects of chemical chaperons
Bohunská, Miroslava ; Pekař, Miloslav (referee) ; Krouská, Jitka (advisor)
This bachelor thesis deals with the study of protective substances against denaturation processes, called chemical chaperones. The theoretical part describes the general characteristics of proteins, description of selected chaperones and methods of differential scanning calorimetry. In the experimental part, the protective effects of four potential protective agents - trehalose, guanidine hydrochloride, 3-hydroxybutyrate and hydroxyectoine - were investigated on the lysozyme model protein. The protective effects of the individual substances were examined by differential scanning calorimetry (DSC), which determined the denaturation temperature of lysozyme in the presence of preservatives. Of all the chemical chaperones examined, the highest protective effect was observed with 3-hydroxybutyrate, which shifted the denaturation temperature to higher levels, and guanidine hydrochloride, which on the other hand lowered the denaturation temperature. At the same time, a reversible denaturation process was found in some substances, which was the most intense in GuHCl.
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Prediction of the Effect of Nucleotide Substitution Using Machine Learning
Šalanda, Ondřej ; Martínek, Tomáš (referee) ; Bendl, Jaroslav (advisor)
This thesis brings a new approach to the prediction of the effect of nucleotide polymorphism on human genome. The main goal is to create a new meta-classifier, which combines predictions of several already implemented software classifiers. The novelty of developed tool lies in using machine learning methods to find consensus over those tools, that would enhance accuracy and versatility of prediction. Final experiments show, that compared to the best integrated tool, the meta-classifier increases the area under ROC curve by 3,4 in average and normalized accuracy is improved by up to 7\,\%. The new classifying service is available at http://ll06.sci.muni.cz:6232/snpeffect/.
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Characterization of Rhodosporidium toruloides proteome using LC-MS/MS
Bruštík, David ; Szotkowski, Martin (referee) ; Zdráhal, Zbyněk (advisor)
Characterization of differentially regulated proteins is crucial for the identification of metabolic pathways and their understanding in connection with the creation of important products of a selected strain of yeast. This diploma thesis focuses on the proteome analysis of the Rhodosporidium toruloides cultivated under different conditions. The metabolism of these yeasts with the characteristics of important metabolites is described in the theoretical part. The next part of the thesis is focused on proteomic approaches and bottom-up proteomics from the sample preparation to mass spectrometry analysis. The experimental part deals with the cultivation of yeast at different C/N ratios, next the isolation and determination of proteins using the FASP method, which includes proteolytic cleavage by trypsin, LC-MS/MS analysis and the database search.
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Multi-Agent System for the Prediction of the Effect of Mutations on Protein Stability
Doseděl, Ondřej ; Martínek, Tomáš (referee) ; Musil, Miloš (advisor)
Proteiny jsou základním stavebním blokem všech žijících organismů, kde jsou zodpovědné za mnoho důležitých procesů. Jsou složeny z řetězců aminokyselin. Tyto řetězce mohou být jakkoliv změněné. Tomuto procesu se říká mutace a může být samovolná nebo indukovaná v laboratoři. Cílem této práce bylo vytvoření nových modelů pro určení stability proteinů. Skládá se ze dvou modelů. První model je multi-agentní systém pro klasifikaci stability proteinů. Nejlepší multi-agentní systém získal přesnost 0.7 a 0.41 MCC. Druhá část se~zabývala predikcí konkrétních hodnot G, kde byl vytvořený Extreme Gradient Boosting model, který získal 1.67 RMSE a 0.53 PCC. Součástí této práce byly představené 2 datasety, které jsou na sobě plně nezávislé, použitelné pro trénování a validaci modelů.
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Human powered electric sources
Naller, Ivan ; Škoda, Jan (referee) ; Baxant, Petr (advisor)
The aim of this work is to map sources of electricity-driven man. It is divided into three parts, the first of which deals with the muscles of the human body and essential components of the diet. The second part includes a search created prototypes of generators from small to big achievements. The last part is focused on the performance that can be achieved in a given individual and the associated energy demands of humanity. After the experiment, it is apparent that the average power of man is in the range of 150 to 300 W. On the basis of the data obtained it is possible to use the energy generated man (in gyms, fitness centers ....) for lighting, or simple applications such as water heating etc.
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Prediction of Protein Solubility
Marušiak, Martin ; Martínek, Tomáš (referee) ; Hon, Jiří (advisor)
Protein solubility is closely related to the usability of proteins in industrial use and research. The successful prediction of solubility would therefore lead to a significant saving of financial resources. This work presents new solubility predictor Solpex based on machine learning that achieved better performance on independent test set than any comparable solubility prediction tool. The predictor implementation was preceded by a study of the biological nature of solubility, evaluation of existing solubility prediction approaches, datasets building, many experiments with novel features and selection of the best features for the predictor. As the most important step in machine learning is the datasets building, this work mainly benefits from own rigorous processing of the main source of solubility data - the TargetTrack database.
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