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Showing 1 to 4 of 4 for “"Pathway-Based Analysis"”.

  1. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data

    … processes, and identifying important pathways related with diseases. We define a "set" as a group of highly-correlated high-dimensional (HCHD) variables that possess a certain practical meaning or control a certain process, and define an "element" as one of the HCHD variables within a …

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  2. Bayesian Hierarchical Latent Model for Gene Set Analysis

    Pathway is a set of genes which are predefined and serve a particular celluar or physiological function. Ranking pathways relevant to a particular phenotype can help researchers focus on a few sets of genes in pathways. In this thesis, a Bayesian hierarchical latent model was proposed using …

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  3. Dimensionality Reduction, Feature Selection and Visualization of Biological Data

    … to dimensionality reduction in genomic analysis and biomarker identification studies are: Feature extraction, creating new features by combining existing ones based on a mapping technique; and feature selection, choosing an optimal subset of all features based on an objective function. …

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  4. Statistical Methods for Genetic Pathway-Based Data Analysis

    … development of the high dimensional genetic data analysis. Many statistical methods for the microarray data analysis consider one gene at a time, but they may miss subtle changes at the single gene level. This limitation may be overcome by considering a set of genes simultaneously where the gene …

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