Dynamic Gaussian graphical models for modelling genomic networks

Mathematics

• Class 16%
• Computational Complexity 26%
• Convex Optimization 29%
• Determinant 23%
• Entire 24%
• Equality Constraints 31%
• Gaussian Model 98%
• Gene 27%
• Genome 31%
• Genomics 100%
• Graphical Models 100%
• Maximum Likelihood Estimation 26%
• Model 9%
• Modeling 55%
• Network Structure 35%
• Partial Correlation 39%
• Pathway 34%
• Penalized Maximum Likelihood 78%
• Positive definite 25%
• Sequencing 33%

Engineering & Materials Science

• Computational complexity 23%
• Convex optimization 30%
• DNA 29%
• Genes 27%
• Genomics 29%
• Maximum likelihood 26%
• Maximum likelihood estimation 32%