Probabilistic Genetic Networks
Mostrando 1-7 de 7 artigos, teses e dissertações.
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1. GENETIC-NEURAL MODEL FOR PORTFOLIO OPTIMIZATION WITH FINANCIAL OPTIONS IN THE BRAZILIAN MARKET / MODELO GENÉTICO-NEURAL PARA OTIMIZAÇÃO DE CARTEIRAS COM OPÇÕES FINANCEIRAS NO MERCADO BRASILEIRO
This dissertation develops an intelligent, quantitative and probabilistic model to determine an optimal composition of a portfolio consisting of a financial asset and options over this asset. Initially we studied the characteristics of the historical distribution of returns and volatility of the most liquid stocks from the BOVESPA Stock Exchange, from Januar
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 08/02/2011
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2. Feature selection and intrinsically multivariate prediction in gene regulatory networks identification / Seleção de características e predição intrinsecamente multivariada em identificação de redes de regulação gênica
Feature selection is a crucial topic in pattern recognition applications, especially in bioinformatics, where problems usually involve data with a large number of variables and small number of observations. The present work addresses feature selection aspects in the problem of gene regulatory network identification from expression profiles. Particularly, we
Publicado em: 2008
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3. Modelagem do controle gênico do ciclo celular por redes genéticas probabilísticas. / Cell-Cycle Genetic Control Modeling by Probabilistic Genetic Networks
O ciclo de divisão celular compreende uma seqüência de fenômenos controlados por una complexa rede de regulação gênica muito estável e robusta. Aplicamos as Redes Genéticas Probabilísticas (PGNs) para construir um modelo cuja dinâmica e robustez se assemelham às observadas no ciclo celular biológico. A estrutura de nosso modelo PGN foi inspirada
Publicado em: 2007
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4. Dimensionality reduction using mean conditional entropy applied for bioinformatics and image processing problems / "Redução de dimensionalidade utilizando entropia condicional média aplicada a problemas de bioinformática e de processamento de imagens"
Dimensionality reduction is a very important pattern recognition problem with many applications. Among the dimensionality reduction techniques, feature selection was the main focus of this research. In general, most dimensionality reduction methods that may be found in the literature privilegiate cases in which the data is linearly separable and with only tw
Publicado em: 2004
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5. BAYESIAN LEARNING FOR NEURAL NETWORKS / APRENDIZADO BAYESIANO PARA REDES NEURAIS
This dissertation investigates the Bayesianan Neural Networks, which is a new approach that merges the potencial of the artificial neural networks with the robust analytical analysis of the Bayesian Statistic. Typically, theconventional neural networks such as backpropagation, have good performance but presents problems of convergence, when enough data for t
Publicado em: 1999
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6. Combining biological networks to predict genetic interactions
Genetic interactions define overlapping functions and compensatory pathways. In particular, synthetic sick or lethal (SSL) genetic interactions are important for understanding how an organism tolerates random mutation, i.e., genetic robustness. Comprehensive identification of SSL relationships remains far from complete in any organism, because mapping these
National Academy of Sciences.
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7. Stochastic mechanisms in gene expression
In cellular regulatory networks, genetic activity is controlled by molecular signals that determine when and how often a given gene is transcribed. In genetically controlled pathways, the protein product encoded by one gene often regulates expression of other genes. The time delay, after activation of the first promoter, to reach an effective level to contro
The National Academy of Sciences of the USA.