Statistical Methods for Microarray Data Analysis : Methods and Protocols /
| Corporate Author: | |
|---|---|
| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
| Published: |
New York, NY :
Springer New York : Imprint: Humana,
2013.
|
| Edition: | 1st ed. 2013. |
| Series: | Methods in Molecular Biology,
972 |
| Subjects: |
Table of Contents:
- What Statisticians Should Know About Microarray Gene Expression Technology
- Where Statistics and Molecular Microarray Experiments Biology Meet
- Multiple Hypothesis Testing: A Methodological Overview
- Gene Selection with the d-sequence Method
- Using of Normalizations for Gene Expression Analysis
- Constructing Multivariate Prognostic Gene Signatures with Censored Survival Data
- Clustering of Gene-Expression Data via Normal Mixture Models
- Network-based Analysis of Multivariate Gene Expression Data
- Genomic Outlier Detection in High-throughput Data Analysis
- Impact of Experimental Noise and Annotation Imprecision on Data Quality in Microarray Experiment
- Aggregation Effect in Microarray Data Analysis
- Test for Normality of the Gene Expression Data.