Princeton University Library Catalog
- New York ; London : Springer, 2009.
- xiv, 149 p. : ill. (some col.) ; 25 cm.
- Related name
- Applied bioinformatics and biostatistics in cancer research. [More in this series]
- Summary note
- "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."--BOOK JACKET.
- Bibliographic references
- Includes bibliographical references and index.
- 1. On the Role and Potential of High-Dimensional Biologic Data in Cancer Research / Ross L. Prentice -- 2. Variable Selection in Regression - Estimation, Prediction, Sparsity, Inference / Jaroslaw Harezlak, Eric Tchetgen and Xiaochun Li -- 3. Multivariate Nonparametric Regression / Charles Kooperberg and Michael LeBlanc -- 4. Risk Estimation / Ronghui Xu and Anthony Gamst -- 5. Tree-Based Methods / Adele Cutler, D. Richard Cutler and John R. Stevens -- 6. Support Vector Machine Classification for High-Dimensional Microarray Data Analysis, With Applications in Cancer Research / Hao Helen Zhang -- 7. Bayesian Approaches: Nonparametric Bayesian Analysis of Gene Expression Data / Sonia Jain.
- 9780387697635 (hbk.)
- 0387697632 (hbk.)
- C - S