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110402s2009 xxu| s |||| 0|eng d |
| 020 |
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|a 9780387697659
|9 978-0-387-69765-9
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| 024 |
7 |
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|a 10.1007/978-0-387-69765-9
|2 doi
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| 100 |
1 |
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|a Li, Xiaochun.
|e editor.
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| 245 |
1 |
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|a High-Dimensional Data Analysis in Cancer Research
|c edited by Xiaochun Li, Ronghui Xu.
|h [electronic resource] /
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| 264 |
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1 |
|a New York, NY :
|b Springer New York,
|c 2009.
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| 300 |
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|a VIII, 392p. 23 illus., 6 illus. in color.
|b online resource.
|
| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Applied Bioinformatics and Biostatistics in Cancer Research
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| 505 |
0 |
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|a 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.
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| 520 |
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|a 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.
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| 650 |
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|a Medicine.
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| 650 |
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|a Oncology.
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| 650 |
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|a Human genetics.
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| 650 |
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|a Medical laboratories.
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|a Microbiology.
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| 650 |
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|a Neurosciences.
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| 650 |
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|a Biomedicine.
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| 650 |
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|a Cancer Research.
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| 650 |
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|a Laboratory Medicine.
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| 650 |
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|a Human Genetics.
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| 650 |
2 |
4 |
|a Medical Microbiology.
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| 650 |
2 |
4 |
|a Molecular Medicine.
|
| 650 |
2 |
4 |
|a Neurosciences.
|
| 700 |
1 |
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|a Xu, Ronghui.
|e editor.
|
| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9780387697635
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| 830 |
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|a Applied Bioinformatics and Biostatistics in Cancer Research
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| 856 |
4 |
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|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-0-387-69765-9
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| 912 |
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|a ZDB-2-SBL
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| 950 |
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|a Biomedical and Life Sciences (Springer-11642)
|