Master thesis deals with dividing destricts of the Czech Republic in to clusters acording to demographic indicators during the year 2011. After the theoretical introduction with exploratory data analyiss, factor analysis and cluster analysis is described practical implementation of agglomerative hierarchical clustering. Within the frame cluster analysis we compare results calculated by four methods of clustering, which are the single linkage method, the complete linkage method, the average linkage method and Ward's method. At the conclusion we select the method which divides destricts of the Czech Republic in to the clusters the best. Master thesis includes a prezentations of discovere results with the help of dendrograms and cartograms. The analysis were carried out with the help of the statistical program STATISTICA.

The topic of my diploma thesis is the statistical evaluation of biological sequences with the help of phylogenic trees. In the theoretical part we will create a literary recherche of estimation methodology concerning the course of phylogeny on the basis of the similarity of biological sequences (DNA and proteins) and we will focus on the inaccuracies of the estimation, their causes and the possibilities of their elimination. Afterwards, we will compare the methods for the statistical evaluation of the correctness of the course of phylogeny. In the practical part of the thesis we will suggest algorithms that will be used for testing the correctness of the phylogenic trees on the basis of bootstrapping, jackknifing, OTU jackknifing and PTP test which are able to the capture phylogenic tree with the method neighbor joining from the biological sequences in FASTA code. It is also possible to change the distance model and the substitution matrix. To be able to use these algorithms for the statistical support of phylogenic trees we have to verify their right function. This verification will be evaluated on the theoretical sequences of the amino acids. For the verification of the correct function of the algorithms, we will carry out single statistical tests on real 10 sequences of mammalian ubiquitin. These results will be analysed and appropriately discussed.

Pattern recognition is an important area with potential applications in computer vision, Speech understanding, knowledge engineering, bio-medical data classification, earth sciences, life sciences, economics, psychology, linguistics, etc. Clustering is an unsupervised classification process corning under the area of pattern recognition. There are two types of clustering approaches: 1) Non-hierarchical methods 2) Hierarchical methods. Non-hierarchical algorithms are iterative in nature and. perform well in the context of isotropic clusters. Time-complexity of these algorithms is order of (0 (n) ) and above, Hierarchical agglomerative algorithms, on the other hand, are effective when clusters are non-isotropic. The single linkage method of hierarchical category produces a dendrogram which corresponds to the minimal spanning tree, conventional approaches are time consuming requiring O (n2 ) computational time. In this thesis we propose an intelligent partitioning scheme for generating the minimal spanning tree in the co-ordinate space. This is computationally elegant as it avoids the computation of similarity between many pairs of samples me minimal spanning tree generated can be used to produce C disjoint clusters by breaking the (C-1) longest edges in the tree. A systolic architecture has been proposed to increase the speed of the algorithm further. Simulation study has been conducted and the corresponding results are reported. The simulation package has been developed on DEC-1090 in Pascal. It is observed based on the simulation study that the parallel implementation reduces the time enormously. The number of processors required for the parallel implementation is a constant making the approach more attractive. Texture analysis and synthesis has been extensively studied in the context of computer vision, Two important approaches which have been studied extensively by researchers earlier are statistical and structural approaches, Texture is understood to be a periodic pattern with primitive sub patterns repeating in a particular fashion. This has been used to characterize texture with the help of the hierarchical data structure, tree. It is convenient to use a tree data structure as, along with the operations like merging, splitting, deleting a node, adding a node, etc, .it would be useful to handle a periodic pattern. Various functions like angular second moment, correlation etc, which are used to characterize texture have been translated into the new language of hierarchical data structure.

Made available in DSpace on 2016-06-02T19:31:55Z (GMT). No. of bitstreams: 1 3610.pdf: 381494 bytes, checksum: 801cdcfd0eb82f33c299301532707d13 (MD5) Previous issue date: 2011-03-04 / Financiadora de Estudos e Projetos / Assuming that traditional measures of diversity are rough predictors of functioning and that measures that incoporate information about functional traits are better predictors than the traditional ones, functional diversity measures are intensely used nowadays. However, whether the inclusion of functional traits in biodiversity estimation indeed increases our predictive power is rarely tested. Moreover, dendrogram-based functional diversity measures usually do not take abundance into account. By sampling a southern cerrado site in Brazil, we tested whether, when compared to traditional diversity measures, the inclusion of functional traits leads to an increased predictive power in relating functional diversity to community functioning. We demonstrated that it is possible to include abundance in dendrogram-based functional diversity, and tested whether, when compared to functional diversity as usually calculated, the inclusion of abundance leads to an increased predictive power. No diversity measure was related to community functioning, including functional diversity. Nevertheless, we showed that it is possible to include abundance in dendrogram16 based functional diversity measures, even if most indices were correlated with each other. / Assumindo que medidas de diversidade tradicionais são estimativas grosseiras do funcionamento de comunidades e que medidas que incorporam informações dos traços funcionais são melhores do que as tradicionais, medidas de diversidade funcional são bastante utilizadas atualmente. Contudo, raramente é testado se, de fato, a inclusão dos traços funcionais em estimativas de biodiversidade aumenta nosso poder preditivo. Além disso, medidas de diversidade funcional baseadas em dendrogramas geralmente não consideram a abundância. Em uma área de cerrado no sudeste brasileiro, testamos se a inclusão dos traços funcionais leva a um aumento no poder preditivo ao relacionar a diversidade funcional ao funcionamento da comunidade quando comparada a medidas de diversidade tradicionais. Demonstramos que é possível incluir a abundância em medidas de diversidade funcional baseadas em dendrogramas e testamos se a inclusão da abundância eleva o poder preditivo da diversidade funcional em comparação à comumente calculada. Nenhuma medida de diversidade relacionou-se ao funcionamento da comunidade, inclusive a diversidade funcional. Porém, mostramos que é possível incluir a abundância em medidas de diversidade funcional baseadas em dendrogramas, apesar da maioria dos índices estar correlacionada.

Made available in DSpace on 2016-01-26T18:56:33Z (GMT). No. of bitstreams: 1 ANA CLAUDIA AMBIEL_Dissertacao Agro.pdf: 1588101 bytes, checksum: 47a54fc705f03fc7d27cd4e4abfdb183 (MD5) Previous issue date: 2007-07-18 / The aim of this work was the determination of intra and intergenetic similarity between three Brachiaria species among germplasm accesses and commercial materials throughout RAPD markers. Seeds were used as DNA source. 10 decamers primers were selected between 120 primers assayed and 107 polymorphic bands were used to perform the molecular variance analysis (AMOVA), Jaccard similarity and species fixation index. 24.4% of the total variability was contained between species and 75.6% inside the species, with a species fixation index (FST) of 0.24. The tree showed that two major branches were formed, one with the three outgroup species and other with the species, this one split in three minor branches one with all B. ruziziensis samples; other with all B. decumbens accessions and three of B. brizantha and the last with two B. brizantha accesses, all commercial cultivars and B. decumbens cv. Basilisk . It was possible to group, throughout RAPD, Brachiaria accesses and cultivars. The genetic variability index between species was considered low and somehow low when faced with autogamous species. B.brizantha showed the highest genetic variability and the lowest FST what means that there is a higher genetic flux intra specific than the others. / O propósito deste trabalho foi determinar a similaridade genética de entre acessos de germoplasma e cultivares comerciais três espécies de Brachiaria (inter e intraespecífica), através de marcadores RAPD. Sementes foram utilizadas como fonte de DNA. 10 primers decâmeros foram selecionados de 120 primers avaliados, produzindo 107 bandas polimórficas, as quais foram utilizados para a análise de variância molecular (AMOVA), o coeficiente de similaridade de Jaccard e índices de fixação gênica. 24,40% da variabilidade genética total está contida entre as espécies e 75,60% dentro destas, com índice de fixação gênica (FST) 0,24. No dendrograma houve a formação de dois ramos, um formado por P. maximum e B. arrecta e o outro subdividido em três: todas amostras de B. ruziziensis; todos os acessos de B. decumbens e três acessos de B. brizantha e o último com dois acessos de B. brizantha mais as B. brizantha comerciais e a B. decumbens cv Basilisk . Foi possível agrupar os acessos e cultivares de Brachiaria através de RAPD. O índice de variabilidade genética entre espécies foi considerado baixo, sendo inferior a valores determinados em algumas espécies autógamas. B. brizantha apresenta maior variabilidade genética e menor FST indicando maior fluxo gênico intra-específico do que as outras.

Made available in DSpace on 2016-07-18T17:51:14Z (GMT). No. of bitstreams: 1 ANA CLAUDIA AMBIEL_Dissertacao Agro.pdf: 1588101 bytes, checksum: 47a54fc705f03fc7d27cd4e4abfdb183 (MD5) Previous issue date: 2007-07-18 / The aim of this work was the determination of intra and intergenetic similarity between three Brachiaria species among germplasm accesses and commercial materials throughout RAPD markers. Seeds were used as DNA source. 10 decamers primers were selected between 120 primers assayed and 107 polymorphic bands were used to perform the molecular variance analysis (AMOVA), Jaccard similarity and species fixation index. 24.4% of the total variability was contained between species and 75.6% inside the species, with a species fixation index (FST) of 0.24. The tree showed that two major branches were formed, one with the three outgroup species and other with the species, this one split in three minor branches one with all B. ruziziensis samples; other with all B. decumbens accessions and three of B. brizantha and the last with two B. brizantha accesses, all commercial cultivars and B. decumbens cv. Basilisk . It was possible to group, throughout RAPD, Brachiaria accesses and cultivars. The genetic variability index between species was considered low and somehow low when faced with autogamous species. B.brizantha showed the highest genetic variability and the lowest FST what means that there is a higher genetic flux intra specific than the others. / O propósito deste trabalho foi determinar a similaridade genética de entre acessos de germoplasma e cultivares comerciais três espécies de Brachiaria (inter e intraespecífica), através de marcadores RAPD. Sementes foram utilizadas como fonte de DNA. 10 primers decâmeros foram selecionados de 120 primers avaliados, produzindo 107 bandas polimórficas, as quais foram utilizados para a análise de variância molecular (AMOVA), o coeficiente de similaridade de Jaccard e índices de fixação gênica. 24,40% da variabilidade genética total está contida entre as espécies e 75,60% dentro destas, com índice de fixação gênica (FST) 0,24. No dendrograma houve a formação de dois ramos, um formado por P. maximum e B. arrecta e o outro subdividido em três: todas amostras de B. ruziziensis; todos os acessos de B. decumbens e três acessos de B. brizantha e o último com dois acessos de B. brizantha mais as B. brizantha comerciais e a B. decumbens cv Basilisk . Foi possível agrupar os acessos e cultivares de Brachiaria através de RAPD. O índice de variabilidade genética entre espécies foi considerado baixo, sendo inferior a valores determinados em algumas espécies autógamas. B. brizantha apresenta maior variabilidade genética e menor FST indicando maior fluxo gênico intra-específico do que as outras.

This master’s thesis is engaged in usage of cluster analysis for ECG signal to separate normal QRS complexes from abnormal ones. For this, it is used two algorithms created in professional computing interface MATLAB. The outputs from this master’s thesis are dendrograms, which divide QRS complexes into abnormal and normal clusters, and Pearson correlation coefficients.

Changes in chromosome number and structure may cause serious diseases. Cytogenetic tests leadin to set of karyotype are done for detecting these abnormalities. Chromosomes are visualised with proper methods and karyotype is made up most often. Manual karyotyping is time-consuming and expensive task. Because of this, researchers have been developing automated karyotyping systems. Karyotyping systems classify chromosomes into classes based on their characteristic features. Overlapping and bent chromosomes are limitations for automatic classification since they ocur at almost every mitosis. Accuracy and reliability of karyotyping systems still depend on the human intervention. Overcoming of these problems and development of fully automated system is the aim of modern approaches.

Protein sequencing has produced overwhelming amount of protein sequences, especially in the last decade. Nevertheless, the majority of the proteins' functional and structural classes are still unknown, and experimental methods currently used to determine these properties are very expensive, laborious and time consuming. Therefore, automated computational methods are urgently required to accurately and reliably predict functional and structural classes of the proteins. Several bioinformatics methods have been developed to determine such properties of the proteins directly from their sequence information. Such methods that involve signal processing methods have recently become popular in the bioinformatics area and been investigated for the analysis of DNA and protein sequences and shown to be useful and generally help better characterise the sequences. However, there are various technical issues that need to be addressed in order to overcome problems associated with the signal processing methods for the analysis of the proteins sequences. Amino acid indices that are used to transform the protein sequences into signals have various applications and can represent diverse features of the protein sequences and amino acids. As the majority of indices have similar features, this project proposes a new set of computationally derived indices that better represent the original group of indices. A study is also carried out that resulted in finding a unique and universal set of best discriminating amino acid indices for the characterisation of allergenic proteins. This analysis extracts features directly from the protein sequences by using Discrete Fourier Transform (DFT) to build a classification model based on Support Vector Machines (SVM) for the allergenic proteins. The proposed predictive model yields a higher and more reliable accuracy than those of the existing methods. A new method is proposed for performing a multiple sequence alignment. For this method, DFT-based method is used to construct a new distance matrix in combination with multiple amino acid indices that were used to encode protein sequences into numerical sequences. Additionally, a new type of substitution matrix is proposed where the physicochemical similarities between any given amino acids is calculated. These similarities were calculated based on the 25 amino acids indices selected, where each one represents a unique biological protein feature. The proposed multiple sequence alignment method yields a better and more reliable alignment than the existing methods. In order to evaluate complex information that is generated as a result of DFT, Complex Informational Spectrum Analysis (CISA) is developed and presented. As the results show, when protein classes present similarities or differences according to the Common Frequency Peak (CFP) in specific amino acid indices, then it is probable that these classes are related to the protein feature that the specific amino acid represents. By using only the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient, as biologically related features can appear individually either in the real or the imaginary spectrum. This is successfully demonstrated over the analysis of influenza neuraminidase protein sequences. Upon identification of a new protein, it is important to single out amino acid responsible for the structural and functional classification of the protein, as well as the amino acids contributing to the protein's specific biological characterisation. In this work, a novel approach is presented to identify and quantify the relationship between individual amino acids and the protein. This is successfully demonstrated over the analysis of influenza neuraminidase protein sequences. Characterisation and identification problem of the Influenza A virus protein sequences is tackled through a Subgroup Discovery (SD) algorithm, which can provide ancillary knowledge to the experts. The main objective of the case study was to derive interpretable knowledge for the influenza A virus problem and to consequently better describe the relationships between subtypes of this virus. Finally, by using DFT-based sequence-driven features a Support Vector Machine (SVM)-based classification model was built and tested, that yields higher predictive accuracy than that of SD. The methods developed and presented in this study yield promising results and can be easily applied to proteomic fields.

This diploma thesis deals with the use of some methods of cluster analysis on the ECG signal in order to sort QRS complexes according to their morphology to normal and abnormal. It is used agglomerative hierarchical clustering and non-hierarchical method K – Means for which an application in Mathworks MATLAB programming equipment was developed. The first part deals with the theory of the ECG signal and cluster analysis, and then the second is the design, implementation and evaluation of the results of the usage of developed software on the ECG signal for the automatic division of QRS complexes into clusters.