467 resultados para arrangiamenti iperpiani, combinatoria, topologia, coomologia


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Pós-graduação em Engenharia Mecânica - FEG

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Ciência e Tecnologia de Materiais - FC

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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Química - IQ

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

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The discovering process of new morbid genes and new target proteins for drugs have been shown to be very costly and laborious. Having in view cutting costs and speeding up this process, we propose, in this work, a new method to determine the gene druggability score and morbidity score, the probabilities of the protein encoded by the gene have the characteristics that make it a new target for drugs and in case of an alteration in that gene, we observed a phenotype that characterizes a genetic based illness. To determine these characteristics, we built, analyzed and determined the characteristics of the topology of the integrated molecular interactions network among human genes containing physical interactions between proteins, metabolic interactions and interactions of transcriptional regulation, and included other data such as level of gene transcription and cellular localization of the protein encoded by the gene. We tested our model in training sets and achieved results equal or better than the ones achieved by similar methods in the literature. Finally, with the purpose of investigating whether the assigned scores resembles the potential druggabilities and morbities of the previously unclassi ed genes, we looked for evidences in biomedical literature supporting the potential druggability and morbidity status of genes with the 10 highest scores. We found clear evidences for 73% and 90% of potential druggable and morbid genes respectively

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The representation of real objects in virtual environments has applications in many areas, such as cartography, mixed reality and reverse engineering. The generation of these objects can be performed through two ways: manually, with CAD (Computer Aided Design) tools, or automatically, by means of surface reconstruction techniques. The simpler the 3D model, the easier it is to process and store it. However, this methods can generate very detailed virtual elements, that can result in some problems when processing the resulting mesh, because it has a lot of edges and polygons that have to be checked at visualization. Considering this context, it can be applied simplification algorithms to eliminate polygons from resulting mesh, without change its topology, generating a lighter mesh with less irrelevant details. The project aimed the study, implementation and comparative tests of simplification algorithms applied to meshes generated through a reconstruction pipeline based on point clouds. This work proposes the realization of the simplification step, like a complement to the pipeline developed by (ONO et al., 2012), that developed reconstruction through cloud points obtained by Microsoft Kinect, and then using Poisson algorithm