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High-dimensional data analysis in cancer research

Author: Xiaochun Li; Ronghui Xu
Publisher: New York : Springer, ©2009.
Series: Applied bioinformatics and biostatistics in cancer research.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
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  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: C Original
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Xiaochun Li; Ronghui Xu
ISBN: 0387697659 9780387697659 9780387697635 0387697632
OCLC Number: 500969712
Description: 1 online resource.
Contents: Introduction --
Multiple comparisons --
marginal model vs. conditonal model --
multivariate nonparametric regression --
Multivariate ROC --
Methods for estimating prediction error --
Trees --
bagging/boosting/model averaging --
SVM and Sparse SVM --
Bayesian --
Appendix.
Series Title: Applied bioinformatics and biostatistics in cancer research.
Responsibility: Xiaochun Li, Ronghui Xu, editors.
More information:

Abstract:

This volume presents the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data. It poses new  Read more...

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