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Character-based methods for DNA barcoding
Kalianková, Kateřina ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
This work deals with character-based DNA barcoding. DNA barcoding and character-based DNA barcoding methods are described in the introduction. Another part contains information of method CAOS (Characteristic Attributes Organization) and method BLOG (Barcoding with LOGic). Programs are described in the practical part. The end contains results.
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Molecular Signature as Optima of Multi-Objective Function with Applications to Prediction in Oncogenomics
Aligerová, Zuzana ; Maděránková, Denisa (referee) ; Provazník, Ivo (advisor)
Náplní této práce je teoretický úvod a následné praktické zpracování tématu Molekulární signatura jako optimální multi-objektivní funkce s aplikací v predikci v onkogenomice. Úvodní kapitoly jsou zaměřeny na téma rakovina, zejména pak rakovina prsu a její podtyp triple negativní rakovinu prsu. Následuje literární přehled z oblasti optimalizačních metod, zejména se zaměřením na metaheuristické metody a problematiku strojového učení. Část se odkazuje na onkogenomiku a principy microarray a také na statistiku a s důrazem na výpočet p-hodnoty a bimodálního indexu. Praktická část je pak zaměřena na konkrétní průběh výzkumu a nalezené závěry, vedoucí k dalším krokům výzkumu. Implementace vybraných metod byla provedena v programech Matlab a R, s využitím dalších programovacích jazyků a to konkrétně programů Java a Python.
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Protein hot spots prediction
Kašpárek, Jan ; Tkacz, Ewaryst (referee) ; Maděránková, Denisa (advisor)
Knowledge of protein hot spots and the ability to successfully predict them while using only primary protein structure has been a worldwide scientific goal for several decades. This thesis describes the importance of hot spots and sums up advances achieved in this field of study so far. Besides that we introduce hot spot prediction algorithm using only a primary protein structure, based primarily on signal processing techniques. To convert protein sequence to numerical signal we use the EIIP attribute, while further processing is carried out via means of S-transform. The algorithm achieves sensitivity of more than 60 %, positive predictive value exceeds 50 % and the main advantage over competitive algorithms is its simplicity and low computational requirements.
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Methods for multialignment of nucleotide sequences
Trněný, Ondřej ; Škutková, Helena (referee) ; Maděránková, Denisa (advisor)
To be able to understand characteristics and purpose of biological sequences correctly, it is crucial to have a possibility to sort and compare them. Because of this need and to extend existing knowledge pool, numerous methods were proposed. Especially in field of multiple sequences alignment. Methods for multiple sequences alignment may provide various valuable information about sequences which failed to show enough similarity in pairwise alignment. According to this, several algorithms were implemented in various computer applications which provide a way to analyse huge sets of data. One of those, the progressive alignment algorithm, is implemented as a part of this thesis
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Fuzzy classification of DNA sequences
Těthal, Jiří ; Maděránková, Denisa (referee) ; Škutková, Helena (advisor)
The work deals with the fuzzy classification of DNA sequences. In the first part the theory summarized information about Fuzzy logic and methods of its use in the classification of biological sequence data. The second part is practically deal with the classification algorithm for assessing the similarity of sequences. Specifically, the dividing of coding and non-coding parts of the sequence and the use of fuzzy classification in DNA barcoding.
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Prediction methods of protein hot spots
Duras, Jan ; Provazník, Ivo (referee) ; Maděránková, Denisa (advisor)
This master's thesis deals with prediction of hot spots in proteins. The theorethical part describes compositions of proteins interfaces and hot spots. There are mentioned basic principles of hot spots prediction. In the practical part is selected method, using the S-Transform, designed to pseudocode and then implmented to Matlab software. Created program is tested on a sample of data and compared with available methods.
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Fourier transformation and spectrogram analysis of DNA sequences
Krejčí, Michal ; Provazník, Ivo (referee) ; Maděránková, Denisa (advisor)
Various methods of DNA sequences modifications for frequency analysis and basic characteristics of DNA are described in the theoretical part of this thesis. Tricolor spectrograms, created by short time Fourier transform help us to recognize some characteristic patterns in DNA sequences. Practical part of this work deals with developed programme which generates spectrograms and analyse them. Last part deals with the analysis of selected sequences of C. elegans genome. Some patterns are related to data of public databases such as NCBI. Various patterns are explained from the biological nature, which relates to chromosome structure and protein coding regions. Another well recognised patterns, tandem repetitions composed of satellites, microsatellites and minisatelites are described by spectrograms as well.
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Graphical representation of DNA and protein sequences
Pražák, Ondřej ; Kolářová, Jana (referee) ; Maděránková, Denisa (advisor)
Modification of DNA sequences and their suitable representation is important part of analysis, comparison and another processing. Goal of this paper is finding of suitable methods for representation of genomic and proteomic sequences. Because there is great number of metods, this paper will introduce only some of them. All selected methods, are described in the first part of this paper and they were programed in Matlab. Selected methods are illustrated on coding sequences of the first exon of the b-globin gene of 11 different species. Results are compared withresults from the original papers. Some methods are capable of another processing like cluster analysis. Output of this paper is comparison of results, gained from different methods, and finding the most suitable one.
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Biosignal processing - clusetr analysis
Příhodová, Petra ; Maděránková, Denisa (referee) ; Kolářová, Jana (advisor)
This thesis deals with the problem with cluster analysis and biosignal classification options. The principle of cluster analysis, methods for calculating distances between objects and the standard process in the implementation of clustering are described in the first part. For biosignals processing,it is necessary to get familiar with the primary parameters of these signals in the following sections of thesis, process biosignals and methods for recording of action potentials described. Based on studying different clustering methods is presented a program with the applied method kmedoid in the next section of this thesis. The steps of this program are described in detail and in the end of thesis functionality is tested on a database of signals ÚBMI.
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Analysis of biological significant substances
Maděránková, Denisa ; Rychtárik, Milan (referee) ; Roleček, Jiří (advisor)
Selected methods of Raman spectroscopy, like surface-enhanced Raman spectroscopy and single molecule Raman spectroscopy, are described in this diploma work. The basis of two methods for numerical modelling of optical properties of micro- and nanoparticles are prefaced. The methods are Discrete Dipole Approximation and Finite Difference Time Domain. Micro- and nanoparticles are used in surface enhanced Raman spectroscopy and other nanospectroscopic methods. Further, the main instrumentation needed for Raman spectroscopy is described. The first part of experimental section of this work is numerical modelling of photonic nanojet that occures behind dielectric microparticles. This phenomenon leads to a new technique of confocal microscopy with Raman spectra measuring. The second experimental section contains results of Raman spectra measurement with beta-carotene and surface-enhanced Raman spectra of beta-carotene in silver-sol solution.
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