Recent technological advances have given cancer researchers the ability to gather vast
amounts of genetic and genomic data from individual patients. These offer tantalizing …

An increasingly important goal in medical research is to extract information from a large
number of variables measured on patients in order to make predictions of disease-related …

I am pleased to provide a brief introduction to this volume of “High-Dimensional Data
Analysis in Cancer Research”. The chapters to follow will focus on data analysis aspects …

In recent years, quick developments in high-throughput biotechnology have enabled
researchers to generate thousands of potentially interesting measurements per subject …

Cancer-genomic data present modeling challenges due to their high-dimensional nature. A
typical dataset consists of several (tens or hundreds, typically the former) tumor samples …

In recent years, breakthroughs in biomedical technology have led to a wealth of data in
which the number of features (for instance, genes on which expression measurements are …

ABSTRACT A variety of prediction methods are used to relate high‐dimensional genome
data with a clinical outcome using a prediction model. Once a prediction model is developed …

Motivated by risk prediction studies with ultra-high dimensional bio markers, we propose a
novel improvement screening methodology. Accurate risk prediction can be quite useful for …

Recent interest in the application of microarray technology focuses on relating gene
expression profiles to censored survival outcome such as patients' overall survival time or …

Data with a huge size present great challenges in modeling, inferences, and computation. In
handling big data, much attention has been directed to settings with “large p small n”, and …