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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)
To determine whether Mycobacterium bovis BCG vaccination would alter gamma interferon (IFN-gamma) mRNA expression in guinea pig cells exposed to Mycobacterium tuberculosis, we cloned a cDNA encoding guinea pig IFN-gamma from a spleen cell cDNA library. The cDNA is composed of 1,110 bp, with an open reading frame encoding a 166-amino-acid protein which shows(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)
BACKGROUND Climate change could increase the number of regions affected by meteorologic disasters. Meteorologic disasters can increase the risk of infectious disease outbreaks, including waterborne and foodborne diseases. Although many outbreaks of waterborne diseases after single disasters have been analyzed, there have not been sufficient studies(More)
This study presents a microtubule that responds to a magnetic field. We made such a structure by incorporating iron oxide nanoparticles during the preparation of the microtubule. We found that the microtubule stretches its body when the magnetic field is applied and easily aligns with the direction of the applied magnetic field by rotating its body. When(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)
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