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Full-Text Articles in Physical Sciences and Mathematics
Reassessment Of Risk Genotypes (Grn, Tmem106b, And Abcc9 Variants) Associated With Hippocampal Sclerosis Of Aging Pathology, Peter T. Nelson, Wang-Xia Wang, Amanda B. Partch, Sarah E. Monsell, Otto Valladares, Sally R. Ellingson, Bernard R. Wilfred, Adam C. Naj, Li-San Wang, Walter A. Kukull, David W. Fardo
Reassessment Of Risk Genotypes (Grn, Tmem106b, And Abcc9 Variants) Associated With Hippocampal Sclerosis Of Aging Pathology, Peter T. Nelson, Wang-Xia Wang, Amanda B. Partch, Sarah E. Monsell, Otto Valladares, Sally R. Ellingson, Bernard R. Wilfred, Adam C. Naj, Li-San Wang, Walter A. Kukull, David W. Fardo
Pathology and Laboratory Medicine Faculty Publications
Hippocampal sclerosis of aging (HS-Aging) is a common high-morbidity neurodegenerative condition in elderly persons. To understand the risk factors for HS-Aging, we analyzed data from the Alzheimer’s Disease Genetics Consortium and correlated the data with clinical and pathologic information from the National Alzheimer’s Coordinating Center database. Overall, 268 research volunteers with HS-Aging and 2,957 controls were included; detailed neuropathologic data were available for all. The study focused on single-nucleotide polymorphisms previously associated with HS-Aging risk: rs5848 ( GRN ), rs1990622 ( TMEM106B ), and rs704180 ( ABCC9 ). Analyses of a subsample that was not previously evaluated (51 HS-Aging cases …
Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg
Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg
Statistics Faculty Publications
BACKGROUND: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together.
RESULTS: We propose a quadratic regression method for identification of differentially expressed genes and classification of genes based on their temporal expression profiles for non-cyclic short time-course microarray data. This method treats time as a continuous variable, therefore preserves actual time information. We applied this method to a microarray time-course study of gene expression at short …