High-Dimensional Data Analysis in Cancer Research

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 canc...

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Bibliographic Details
Call Number:Libro Electrónico
Corporate Author: SpringerLink (Online service)
Other Authors: Li, Xiaochun (Editor), Xu, Ronghui (Editor)
Format: Electronic eBook
Language:Inglés
Published: New York, NY : Springer New York : Imprint: Springer, 2009.
Edition:1st ed. 2009.
Series:Applied Bioinformatics and Biostatistics in Cancer Research,
Subjects:
Cancer.
Medicine-Research.
Biology-Research.
Medical genetics.
Medical microbiology.
Neurosciences.
Cancer Biology.
Biomedical Research.
Medical Genetics.
Medical Microbiology.
Neuroscience.
Online Access:Texto Completo
Table of Contents:
  • On the Role and Potential of High-Dimensional Biologic Data in Cancer Research
  • Variable selection in regression - estimation, prediction,sparsity, inference
  • Multivariate Nonparametric Regression
  • Risk Estimation
  • Tree-Based Methods
  • Support Vector Machine Classification for High Dimensional Microarray Data Analysis, With Applications in Cancer Research
  • Bayesian Approaches: Nonparametric Bayesian Analysis of Gene Expression Data.

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