Bayesian Selection and Clustering of Polymorphisms in Functionally Related Genes
By David B. Dunson, A. Herring, Stephanie M. Engel. 2008
98 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/285b82c69b0553df661ef41e1b41908fc5830d38
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Andrew Gelman
- Lawrence Carin
- Yu-Sung Su
- David B. Dunson
- Enrique ter Horst
- Abel Rodríguez
- Ya Xue
- David M. Blei
In Genetics
- Enrique ter Horst
- Abel Rodríguez
- Lawrence Carin
- Ya Xue
- Andrew Gelman
- Aleks Jakulin
- David B. Dunson
- Yu-Sung Su
In Molecular Biology
- Enrique ter Horst
- Abel Rodríguez
- Lawrence Carin
- Ya Xue
- Andrew Gelman
- David B. Dunson
- Yu-Sung Su
- David M. Blei
Citations in the corpus
- A weakly informative default prior distribution for logistic and other regression models (2008, result): “Such a large change might seem disturbing, but for the reasons discussed above, we would doubt the effect to be as large as 10.2 on the logistic scale, and the analysis shows these data to be consistent with the much smaller effect size of 5.4.”
- The Matrix Stick-Breaking Process (2008, methodology): “Dunson, Herring, and Mulherin-Engel (2008) used the DP to borrow information across functionally related genes in assessing the health impact of single-nucleotide polymorphisms.”
- Bayesian dynamic density estimation (2008, methodology): “…work has started to develop methods for dependent distributions, either by forming convex combinations of independent processes (Müller et al. 2004; Dunson et al. 2007b; Griffin and Steel 2007; Dunson 2006) or by introducing dependence in the elements of the stick-breaking representation of the…”