Kyeong Eun Lee

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UNLABELLED Selection of significant genes via expression patterns is an important problem in microarray experiments. Owing to small sample size and the large number of variables (genes), the selection process can be unstable. This paper proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent variables to specialize the model(More)
2-(Trimethylammonium) ethyl (R)-3-methoxy-3-oxo-2-stearamidopropyl phosphate [(R)-TEMOSPho], a derivative of an organic chemical identified from a natural product library, promotes highly efficient megakaryopoiesis. Here, we show that (R)-TEMOSPho blocks osteoclast maturation from progenitor cells of hematopoietic origin, as well as blocking the resorptive(More)
Bayesian Models for DNA Microarray Data Analysis. Selection of significant genes via expression patterns is important in a microarray problem. Owing to small sample size and large number of variables (genes), the selection process can be unstable. This research proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent variables(More)
Over the past decade much statistical research has been carried out to develop models for correlated survival data; however, methods for model selection are still very limited. A stochastic search variable selection (SSVS) approach under the proportional hazards mixed-effects model (PHMM) is developed. The SSVS method has previously been applied to linear(More)
The Na,K-ATPase is a heterodimer consisting of an alpha and a beta subunit, which exchanges intracellular Na+ for extracellular K+ using the energy of ATP hydrolysis. Several studies have demonstrated that the enzyme exists as an (alphabeta)2 heterotetramer, an oligomer of alphabeta dimers within the cell membrane, at least during some portion of the(More)
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