Pages that link to "Item:Q5229891"
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The following pages link to Bayesian Hierarchical Varying-Sparsity Regression Models with Application to Cancer Proteogenomics (Q5229891):
Displaying 7 items.
- A Bayesian precision medicine framework for calibrating individualized therapeutic indices in cancer (Q2080717) (← links)
- Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics (Q2195280) (← links)
- Subject-specific Dirichlet-multinomial regression for multi-district microbiota data analysis (Q2686051) (← links)
- Bayesian data integration and variable selection for pan‐cancer survival prediction using protein expression data (Q5128803) (← links)
- Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data (Q6071297) (← links)
- Individualized causal discovery with latent trajectory embedded Bayesian networks (Q6589265) (← links)
- Tumor heterogeneity estimation for radiomics in cancer (Q6617421) (← links)
