Screening for changes in gene expression across biological conditions using high throughput technologies is now common in biology. In this paper we present a broad Bayesian multilevel framework for developing computationally fast shrinkage-based screening tools for this purpose. Our scheme makes it easy to adapt the choice of statistics to the goals of the analysis and to the genomic distributions of signal and noise. We empirically investigate the extent to which these shrinkage-based statistics improve performance, and the situations in which such improvements are larger. Our evaluation uses both extensive simulations and controlled biological experiments. The experimental data include a socalled spike-in experiment, in which the target biological signal is known, and a two-sample experiment, which illustrates the typical conditions in which the methods are applied. Screening for Differentially Expressed Genes: Are Multilevel Models Helpful?: Dongmei Liu, Giovanni Parmigiani and Brian Caffo. In the growing environment, they are many journals in various organisations. Only a very few journals maintain high standards in terms of the content they publish, one has to be careful while picking information as content that is not reliable and untrue can be harmful to research as well as society. Generally, journals can be rated by considering impact factor, reputation of authors, editorial board members and also in terms of the fee they charge. Only high indexing journals have quality articles.
Last date updated on December, 2020