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High-Dimensional Data Analysis in Cancer Research

  • Xiaochun Li
  • Ronghui Xu

Table of contents

  1. Front Matter
    Pages 1-13
  2. Jaroslaw Harezlak, Eric Tchetgen, Xiaochun Li
    Pages 1-21
  3. Charles Kooperberg, Michael LeBlanc
    Pages 1-24
  4. Ronghui Xu, Anthony Gamst
    Pages 1-23
  5. Adele Cutler, D. Richard Cutler, John R. Stevens
    Pages 1-19
  6. Back Matter
    Pages 1-8

About this book

Introduction

With the advent of high-throughput technologies, various types of high-dimensional data have been generated in recent years for the understanding of biological processes, especially processes that relate to disease occurrence or management of cancer.  Motivated by these important applications in cancer research, there has been a dramatic growth in the development of statistical methodology in the analysis of high-dimensional data, particularly related to regression model selection, estimation and prediction.

High-Dimensional Data Analysis in Cancer Research, edited by Xiaochun Li and Ronghui Xu, is a collective effort to showcase statistical innovations for meeting the challenges and opportunities uniquely presented by the analytical needs of high-dimensional data in cancer research, particularly in genomics and proteomics.  All the chapters included in this volume contain interesting case studies to demonstrate the analysis methodology.

High-Dimensional Data Analysis in Cancer Research is an invaluable reference for
researchers, statisticians, bioinformaticians, graduate students and data analysts working in the fields of cancer research.

Keywords

Bayesian Approaches High-Dimensional Biologic data Laboratory Microarray Multivariate Nonparametric Regression Risk Estimation Tree-based Methods Vector bioinformatics cancer research classification gene expression genes oncology proteomics

Editors and affiliations

  • Xiaochun Li
    • 1
  • Ronghui Xu
    • 2
  1. 1.School of Medicine, Division of BiostatisticsIndiana UniversityIndianapolisU.S.A.
  2. 2.Dept. MathematicsUniversity of California, San DiegoLa JollaU.S.A.

Bibliographic information