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- 254 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Big Data Analytics in Oncology with R
Book details
Table of contents
Citations
About This Book
Big Data Analytics in Oncology with R serves the analytical approaches for big data analysis. There is huge progressed in advanced computation with R. But there are several technical challenges faced to work with big data. These challenges are with computational aspect and work with fastest way to get computational results. Clinical decision through genomic information and survival outcomes are now unavoidable in cutting-edge oncology research. This book is intended to provide a comprehensive text to work with some recent development in the area.
Features:
- Covers gene expression data analysis using R and survival analysis using R
- Includes bayesian in survival-gene expression analysis
- Discusses competing-gene expression analysis using R
- Covers Bayesian on survival with omics data
This book is aimed primarily at graduates and researchers studying survival analysis or statistical methods in genetics.
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Yes, you can access Big Data Analytics in Oncology with R by Atanu Bhattacharjee in PDF and/or ePUB format, as well as other popular books in Matemáticas & Probabilidad y estadística. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover Page
- Half-Title Page
- Title Page
- Copyright Page
- Dedication Page
- Contents
- Preface
- Author
- 1 Survival Analysis
- 2 Cox Proportional Survival Analysis
- 3 Parametric Survival Analysis
- 4 Competing Risk Modeling in High Dimensional Data
- 5 Biomarker Thresholding in High Dimensional Data
- 6 High Dimensional Survival Data Analysis
- 7 Frailty Models
- 8 Time-Course Gene Expression Data Analysis
- 9 Survival Analysis and Time-course Data Analysis
- 10 Features Selection in High Dimensional Time to Event Data
- Bibliography
- Index