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Selecting informative genes from microarray experiments is one of the most important data analysis steps for deciphering biological information imbedded in such experiments. However, due to the characteristics of microarray technology and the underlying biology, namely large number of genes and limited number of samples, the statistical soundness of gene(More)
Low density lipoprotein (LDL) and beta-very low density lipoprotein (beta-VLDL) are internalized by the same receptor in mouse peritoneal macrophages and yet their endocytic patterns differ; beta-VLDL is targeted to both widely distributed and perinuclear vesicles, whereas LDL is targeted almost entirely to perinuclear lysosomes. This endocytic divergence(More)
Gene selection is usually the crucial first step in microarray data analysis. One class of typical approaches is to calculate some discriminative scores using data associated with a single gene. Such discriminative scores are then sorted and top ranked genes are selected for further analysis. However, such an approach will result in redundant gene set since(More)
This demonstration will be presented at the 2003 National Conference on Digital Government Research to accompany a short paper entitled " Integration of Multi-Source Spatial Information for Coastal Management and Decision Making ". The demonstration presents the two-year outcomes of our Digital Government project " Digitalization of Coastal Management and(More)
Gene Selection is one class of most used data analysis algorithms on microarray datasets. The goal of gene selection algorithms is to filter out a small set of informative genes that best explains experimental variations. Traditional gene selection algorithms are mostly single-gene based. Some discriminative scores are calculated and sorted for each gene.(More)
Previous studies have proven that it is feasible to build sample classifiers using gene expression profiles. To build an effective sample classifier, dimension reduction process is necessary since classic pattern recognition algorithms do not work well in high dimensional space. In this paper, we present a novel feature extraction algorithm by integrating(More)
Gene Selection is one class of most used data analysis algorithms on microarray dataset. The goal of gene selection algorithms is to filter out a small set of informative genes that best explains experimental variations. Traditional gene selection algorithms are mostly single-gene based. Some discriminative scores are calculated and sorted for each gene.(More)
The aim of this study was to detect the abnormality of the brain functional connectivity of the hypothalamus during acute spontaneous cluster headache (CH) attacks ('in attack') and headache-free intervals ('out of attack') using resting-state functional magnetic resonance imaging (RS-fMRI) technique. The RS-fMRI data from twelve male CH patients during 'in(More)
Hypercholesterolemic rabbit beta-VLDL and human LDL are both internalized by mouse peritoneal macrophages by receptor-mediated endocytosis. However, only beta-VLDL (which binds to the cells with a much higher affinity than LDL) markedly stimulates acyl-CoA/cholesterol acyl transferase (ACAT) and induces foam cell formation in these cells. As an initial step(More)
Macrophage acyl-CoA:cholesterol O-acyltransferase (ACAT), a key enzyme in atheroma foam cell formation, is stimulated by lipoproteins only after a "threshold" amount of cholesterol has accumulated in the cell. The present study explores the hypothesis that cellular sphingomyelin, by increasing the capacity of the cell to accommodate excess cholesterol, can(More)