897 resultados para DNA Sequence, Hidden Markov Model, Bayesian Model, Sensitive Analysis, Markov Chain Monte Carlo


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In this paper is presented a region-based methodology for Digital Elevation Model segmentation obtained from laser scanning data. The methodology is based on two sequential techniques, i.e., a recursive splitting technique using the quad tree structure followed by a region merging technique using the Markov Random Field model. The recursive splitting technique starts splitting the Digital Elevation Model into homogeneous regions. However, due to slight height differences in the Digital Elevation Model, region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Markov Random Field model is applied to the previously segmented data. The resulting regions are firstly structured by using the so-called Region Adjacency Graph. Each node of the Region Adjacency Graph represents a region of the Digital Elevation Model segmented and two nodes have connectivity between them if corresponding regions share a common boundary. Next it is assumed that the random variable related to each node, follows the Markov Random Field model. This hypothesis allows the derivation of the posteriori probability distribution function whose solution is obtained by the Maximum a Posteriori estimation. Regions presenting high probability of similarity are merged. Experiments carried out with laser scanning data showed that the methodology allows to separate the objects in the Digital Elevation Model with a low amount of fragmentation.

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Includes bibliography

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Background: Uterine Leiomyomas (ULs) are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs). Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs. Methodology: We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC) and gene expression microarrays (SAM). The CONEXIC algorithm was applied to integrate the data. Principal Findings: The integrated analysis identified the top 30 significant genes (P<0.01), which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively) and IGFBP5 (P = 0.0002 and P = 0.006, respectively) were up-regulated in the tumours when compared with the adjacent normal myometrium. Conclusions: The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs. © 2013 Cirilo et al.

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In this study, we describe the cDNA cloning, sequencing, and 3-D structure of the allergen hyaluronidase from Polybia paulista venom (Pp-Hyal). Using a proteomic approach, the native form of Pp-Hyal was purified to homogeneity and used to produce a Pp-specific polyclonal antibody. The results revealed that Pp-Hyal can be classified as a glycosyl hydrolase and that the full-length Pp-Hyal cDNA (1315 bp; GI: 302201582) is similar (80-90%) to hyaluronidase from the venoms of endemic Northern wasp species. The isolated mature protein is comprised of 338 amino acids, with a theoretical pI of 8.77 and a molecular mass of 39,648.8 Da versus a pI of 8.13 and 43,277.0 Da indicated by MS. The Pp-Hyal 3D-structural model revealed a central core (α/β)7 barrel, two sulfide bonds (Cys 19-308 and Cys 185-197), and three putative glycosylation sites (Asn79, Asn187, and Asn325), two of which are also found in the rVes v 2 protein. Based on the model, residues Ser299, Asp107, and Glu109 interact with the substrate and potential epitopes (five conformational and seven linear) located at surface-exposed regions of the structure. Purified native Pp-Hyal showed high similarity (97%) with hyaluronidase from Polistes annularis venom (Q9U6V9). Immunoblotting analysis confirmed the specificity of the Pp-Hyal-specific antibody as it recognized the Pp-Hyal protein in both the purified fraction and P. paulista crude venom. No reaction was observed with the venoms of Apis mellifera, Solenopsis invicta, Agelaia pallipes pallipes, and Polistes lanio lanio, with the exception of immune cross-reactivity with venoms of the genus Polybia (sericea and ignobilis). Our results demonstrate cross-reactivity only between wasp venoms from the genus Polybia. The absence of cross-reactivity between the venoms of wasps and bees observed here is important because it allows identification of the insect responsible for sensitization, or at least of the phylogenetically closest insect, in order to facilitate effective immunotherapy in allergic patients. © 2013 Elsevier Ltd.

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Current research compares the Bayesian estimates obtained for the parameters of processes of ARCH family with normal and Student's t distributions for the conditional distribution of the return series. A non-informative prior distribution was adopted and a reparameterization of models under analysis was taken into account to map parameters' space into real space. The procedure adopts a normal prior distribution for the transformed parameters. The posterior summaries were obtained by Monte Carlo Markov Chain (MCMC) simulation methods. The methodology was evaluated by a series of Bovespa Index returns and the predictive ordinate criterion was employed to select the best adjustment model to the data. Results show that, as a rule, the proposed Bayesian approach provides satisfactory estimates and that the GARCH process with Student's t distribution adjusted better to the data.

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Fig (Ficus carica) breeding programs that use conventional approaches to develop new cultivars are rare, owing to limited genetic variability and the difficulty in obtaining plants via gamete fusion. Cytosine methylation in plants leads to gene repression, thereby affecting transcription without changing the DNA sequence. Previous studies using random amplification of polymorphic DNA and amplified fragment length polymorphism markers revealed no polymorphisms among select fig mutants that originated from gamma-irradiated buds. Therefore, we conducted methylation-sensitive amplified polymorphism analysis to verify the existence of variability due to epigenetic DNA methylation among these mutant selections compared to the main cultivar 'Roxo-de-Valinhos'. Samples of genomic DNA were double-digested with either HpaII (methylation sensitive) or MspI (methylation insensitive) and with EcoRI. Fourteen primer combinations were tested, and on an average, non-methylated CCGG, symmetrically methylated CmCGG, and hemimethylated hmCCGG sites accounted for 87.9, 10.1, and 2.0%, respectively. MSAP analysis was effective in detecting differentially methylated sites in the genomic DNA of fig mutants, and methylation may be responsible for the phenotypic variation between treatments. Further analyses such as polymorphic DNA sequencing are necessary to validate these differences, standardize the regions of methylation, and analyze reads using bioinformatic tools. © FUNPEC-RP.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Sistema Texto-Fala (TTS) é atualmente uma tecnologia madura que é utilizada em muitas aplicações. Alguns módulos de um sistema TTS são dependentes do idioma e, enquanto existem muitos recursos disponíveis para a língua inglesa, os recursos para alguns idiomas ainda são limitados. Este trabalho descreve o desenvolvimento de um sistema TTS completo para português brasileiro (PB), o qual também apresenta os recursos já disponíveis. O sistema usa a plataforma MARY e o processo de síntese da voz é baseado em cadeias escondidas de Markov (HMM). Algumas das contribuições deste trabalho consistem na implementação de silabação, determinação da sílaba tônica e conversão grafema-fonema (G2P). O trabalho também descreve as etapas para a organização dos recursos desenvolvidos e a criação de uma voz em PB junto ao MARY. Estes recursos estão disponíveis e facilita a pesquisa na normalização de texto e síntese baseada em HMM par o PB.

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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)