870 resultados para Tree Database
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The phylogeny is one of the main activities of the modern taxonomists and a way to reconstruct the history of the life through comparative analysis of these sequences stored in their genomes aimed find any justification for the origin or evolution of them. Among the sequences with a high level of conservation are the genes of repair because it is important for the conservation and maintenance of genetic stability. Hence, variations in repair genes, as the genes of the nucleotide excision repair (NER), may indicate a possible gene transfer between species. This study aimed to examine the evolutionary history of the components of the NER. For this, sequences of UVRA, UVRB, UVRC and XPB were obtained from GenBank by Blast-p, considering 10-15 as cutoff to create a database. Phylogenetic studies were done using algorithms in PAUP programs, BAYES and PHYLIP package. Phylogenetic trees were build with protein sequences and with sequences of 16S ribosomal RNA for comparative analysis by the methods of parsimony, likelihood and Bayesian. The XPB tree shows that archaeal´s XPB helicases are similar to eukaryotic helicases. According to this data, we infer that the eukaryote nucleotide excision repair system had appeared in Archaea. At UVRA, UVRB and UVRC trees was found a monophyletic group formed by three species of epsilonproteobacterias class, three species of mollicutes class and archaeabacterias of Methanobacteria and Methanococci classes. This information is supported by a tree obtained with the proteins, UVRA, UVRB and UVRC concatenated. Thus, although there are arguments in the literature defending the horizontal transfer of the system uvrABC of bacteria to archaeabacterias, the analysis made in this study suggests that occurred a vertical transfer, from archaeabacteria, of both the NER genes: uvrABC and XPs. According the parsimony, this is the best way because of the occurrence of monophyletic groups, the time of divergence of classes and number of archaeabacterias species with uvrABC system
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The main goal of our research was to search for SSRs in the Eucalyptus EST FORESTs database (using a software for mining SSR-motifs). With this objective, we created a database for cataloging Eucalyptus EST-derived SSRs, and developed a bioinformatics tool, named Satellyptus, for finding and analyzing microsatellites in the Eucalyptus EST database. The search for microsatellites in the FORESTs database containing 71,115 Eucalyptus EST sequences (52.09 Mb) revealed 20,530 SSRs in 15,621 ESTs. The SSR abundance detected on the Eucalyptus ESTs database (29% or one microsatellite every four sequences) is considered very high for plants. Amongst the categories of SSR motifs, the dimeric (37%) and trimeric ones (33%) predominated. The AG/CT motif was the most frequent (35.15%) followed by the trimeric CCG/CGG (12.81%). From a random sample of 1,217 sequences, 343 microsatellites in 265 SSR-containing sequences were identified. Approximately 48% of these ESTs containing microsatellites were homologous to proteins with known biological function. Most of the microsatellites detected in Eucalyptus ESTs were positioned at either the 5 or 3 end. Our next priority involves the design of flanking primers for codominant SSR loci, which could lead to the development of a set of microsatellite-based markers suitable for marker-assisted Eucalyptus breeding programs.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The objective of the researches in artificial intelligence is to qualify the computer to execute functions that are performed by humans using knowledge and reasoning. This work was developed in the area of machine learning, that it s the study branch of artificial intelligence, being related to the project and development of algorithms and techniques capable to allow the computational learning. The objective of this work is analyzing a feature selection method for ensemble systems. The proposed method is inserted into the filter approach of feature selection method, it s using the variance and Spearman correlation to rank the feature and using the reward and punishment strategies to measure the feature importance for the identification of the classes. For each ensemble, several different configuration were used, which varied from hybrid (homogeneous) to non-hybrid (heterogeneous) structures of ensemble. They were submitted to five combining methods (voting, sum, sum weight, multiLayer Perceptron and naïve Bayes) which were applied in six distinct database (real and artificial). The classifiers applied during the experiments were k- nearest neighbor, multiLayer Perceptron, naïve Bayes and decision tree. Finally, the performance of ensemble was analyzed comparatively, using none feature selection method, using a filter approach (original) feature selection method and the proposed method. To do this comparison, a statistical test was applied, which demonstrate that there was a significant improvement in the precision of the ensembles
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Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Casearia sylvestris Sw. is a widespread neotropical tree utilized in popular medicine. Recent research ranked Casearia as one of the most promising genus in the search of drugs against cancer. Despite its wide distribution and pharmacological importance, no microsatellite markers have yet been developed for this genus. In this study, we provide 10 polymorphic microsatellite loci specifically designed for C. sylvestris, used to analyse 90 individuals distributed in two populations from São Paulo state, Brazil. on average, 12.3 alleles per locus were identified, showing the ability of the markers to detect microsatellite polymorphism in this species.