Incorporating biological information in sparse principal component analysis with application to genomic data

Keyphrases

• Genomic Data 100%
• Biological Information 100%
• Sparse Principal Component Analysis 100%
• Principal Coordinate Analysis (PCoA) 57%
• Glioblastoma 28%
• Feature Selection 28%
• Graph Structure 28%
• High Sensitivity 14%
• Complex Disease 14%
• Pattern Recognition 14%
• Simulation Study 14%
• Dimensionality Reduction 14%
• Biological Mechanisms 14%
• Multiple Genes 14%
• High Specificity 14%
• Regression Analysis 14%
• Gene Expression Data 14%
• Performance Prediction 14%
• Misspecified 14%
• Selection Performance 14%
• Component Loadings 14%
• Pattern Visualization 14%
• Feature Prediction 14%
• High-dimensional Data Visualization 14%
• Popular 14%
• Reduction Pattern 14%

Computer Science

• Principal Components 100%
• Component Analysis 100%
• Feature Selection 44%
• Feature Extraction 22%
• High Dimensional Data 11%
• Dimensionality Reduction 11%
• Complex Disease 11%
• Simulation Study 11%
• Prediction Performance 11%
• Pattern Recognition 11%

Biochemistry, Genetics and Molecular Biology

• Principal Component Analysis 100%
• Genomics 100%
• Feature Extraction 25%
• Dimensionality Reduction 12%
• Gene Expression 12%
• Pattern Recognition 12%