Applied Statistics

Data from Stanford University Advance Knowledge in Applied Statistics

Published in Cancer Weekly, August 30th, 2011

2011 AUG 30 -- According to the authors of recent research from Stanford, California, "We propose a hierarchical Bayesian model for analysing gene expression data to identify pathways differentiating between two biological states (e. g. cancer versus non-cancer). Finding significant pathways can improve our understanding of normal and pathological processes and can lead to more effective treatments."

"Our method, Bayesian gene set analysis, evaluates the statistical significance of a specific pathway by using the posterior distribution of its corresponding hyperparameter. We apply Bayesian gene set analysis to a gene expression microarray data set on 50...

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Source: Cancer Weekly (2011-08-30)

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