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...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Li, Xiaochun (Editor ), Xu, Ronghui (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Colección:Applied Bioinformatics and Biostatistics in Cancer Research,
Temas:
Cancer.
Medicine-Research.
Biology-Research.
Medical genetics.
Medical microbiology.
Neurosciences.
Cancer Biology.
Biomedical Research.
Medical Genetics.
Medical Microbiology.
Neuroscience.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

Ejemplares similares