Methods of Microarray Data Analysis IV
As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments. The CAMDA conference plays a role in this evolving field by providing a forum in which investors can analyze the same data sets using different methods. METHODS OF MICROARRAY DAT...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer US
2005, 2005
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| Edition: | 1st ed. 2005 |
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| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Cancer: Clinical Challenges and Opportunities
- Gene Expression Data and Survival Analysis
- The Needed Replicates of Arrays in Microarray Experiments for Reliable Statistical Evaluation
- Pooling Information Across Different Studies and Oligonucleotide Chip Types to Identify Prognostic Genes for Lung Cancer
- Application of Survival and Meta-analysis to Gene Expression Data Combined from Two Studies
- Making Sense of Human Lung Carcinomas Gene Expression Data: Integration and Analysis of Two Affymetrix Platform Experiments
- Entropy and Survival-based Weights to Combine Affymetrix Array Types and Analyze Differential Expression and Survival
- Associating Microarray Data with a Survival Endpoint
- Differential Correlation Detects Complex Associations Between Gene Expression and Clinical Outcomes in Lung Adenocarcinomas
- Probabilistic Lung Cancer Models Conditioned on Gene Expression Microarray Data
- Integration of Microarray Data for a Comparative Study of Classifiers and Identification of Marker Genes
- Use of Micro Array Data via Model-based Classification in the Study and Prediction of Survival from Lung Cancer
- Microarray Data Analysis of Survival Times of Patients with Lung Adenocarcinomas Using ADC and K-Medians Clustering
- Higher Dimensional Approach for Classification of Lung Cancer Microarray Data
- Microarray Data Analysis Using Neural Network Classifiers and Gene Selection Methods
- A Combinatorial Approach to the Analysis of Differential Gene Expression Data
- Genes Associated with Prognosis in Adenocarcinoma Across Studies at Multiple Institutions