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. Molecular Biology mostly welcomes novel manuscripts with novel ideas for the welfare of the human race. Generally, these publications appreciate articles those that are accessible even to those people who are not specialist in the field but are interested in those research topic. These journals are periodical publications that are intended to share the progress of science. Molecular Biology is one of the top Peer-reviewed open access Journals that emphasises molecular aspects. It publishes original research articles, novel, and scientifically sound findings dealing with many different topics.
Last date updated on November, 2020