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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Shoemaker, Jennifer S. (Editor ), Lin, Simon M. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer US : Imprint: Springer, 2005.
Edición:1st ed. 2005.
Temas:
Medical genetics.
Cancer.
Medical Genetics.
Cancer Biology.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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