Applied Bioinformatics and Biostatistics in Cancer Research

High-Dimensional Data Analysis in Cancer Research

Editors: Li, Xiaochun, Xu, Ronghui (Eds.)

  • Poses new challenges and calls for scalable solutions to the analysis of such high dimensional data
  • Presents the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data
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eBook $149.00
price for USA (gross)
  • ISBN 978-0-387-69765-9
  • Digitally watermarked, DRM-free
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  • Immediate eBook download after purchase
Hardcover $199.00
price for USA
  • ISBN 978-0-387-69763-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $199.00
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  • ISBN 978-1-4419-2414-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

Table of contents (7 chapters)

  • Support Vector Machine Classification for High Dimensional Microarray Data Analysis, With Applications in Cancer Research

    Zhang, Hao Helen

    Pages 1-24

  • Bayesian Approaches: Nonparametric Bayesian Analysis of Gene Expression Data

    Jain, Sonia

    Pages 1-20

  • On the Role and Potential of High-Dimensional Biologic Data in Cancer Research

    Prentice, Ross L.

    Pages 1-11

  • Tree-Based Methods

    Cutler, Adele (et al.)

    Pages 1-19

  • Multivariate Nonparametric Regression

    Kooperberg, Charles (et al.)

    Pages 1-24

Buy this book

eBook $149.00
price for USA (gross)
  • ISBN 978-0-387-69765-9
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $199.00
price for USA
  • ISBN 978-0-387-69763-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $199.00
price for USA
  • ISBN 978-1-4419-2414-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
High-Dimensional Data Analysis in Cancer Research
Editors
  • Xiaochun Li
  • Ronghui Xu
Series Title
Applied Bioinformatics and Biostatistics in Cancer Research
Copyright
2009
Publisher
Springer-Verlag New York
Copyright Holder
Springer-Verlag New York
eBook ISBN
978-0-387-69765-9
DOI
10.1007/978-0-387-69765-9
Hardcover ISBN
978-0-387-69763-5
Softcover ISBN
978-1-4419-2414-8
Series ISSN
2363-9644
Edition Number
1
Number of Pages
VIII, 392
Number of Illustrations and Tables
17 b/w illustrations, 6 illustrations in colour
Topics