An under-appreciated aspect of the genetic analysis of gene expression is the impact of post-
probe level normalization on biological inference. Here we contrast nine different methods …

Motivation: Prior to applying genomic predictors to clinical samples, the genomic data must
be properly normalized to ensure that the test set data are comparable to the data upon …

Gene expression analysis is a widely used and powerful method for investigating the
transcriptional behavior of biological systems, for classifying cell states in disease, and for …

Large-scale gene expression measurement techniques provide a unique opportunity to gain
insight into biological processes under normal and pathological conditions. To interpret the …

An attractive application of expression technologies is to predict drug efficacy or safety using
expression data of biomarkers. To evaluate the performance of various classification …

Background With the increasing number of expression profiling technologies, researchers
today are confronted with choosing the technology that has sufficient power with minimal …

RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity,
but lack of reproducibility has hindered their application. A key challenge in the data …

This book combines the experience of 225 experts on 900 pages. Scientists worldwide are
currently overwhelmed by the ever-increasing number and diversity of genome projects …

Background'Fold-change'cutoffs have been widely used in microarray assays to identify
genes that are differentially expressed between query and reference samples. More …

One of the major issues in expression profiling analysis still is to outline proper thresholds to
determine differential expression, while avoiding false positives. The problem being that the …