scholarly journals A Bayesian model selection approach for identifying differentially expressed transcripts from RNA sequencing data

2017 ◽  
Vol 67 (1) ◽  
pp. 3-23 ◽  
Author(s):  
Panagiotis Papastamoulis ◽  
Magnus Rattray
Keyword(s):  
Model Selection ◽  
Rna Sequencing ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Model Selection Approach ◽  
Selection Approach ◽  
Bayesian Model Selection Approach

scholarly journals The Continual Reassessment Method for Multiple Toxicity Grades: A Bayesian Model Selection Approach

PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e98147 ◽  
Author(s):  
Haitao Pan ◽  
Cailin Zhu ◽  
Feng Zhang ◽  
Ying Yuan ◽  
Shemin Zhang ◽  
...  
Keyword(s):  
Model Selection ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Continual Reassessment Method ◽  
Model Selection Approach ◽  
Continual Reassessment ◽  
Selection Approach ◽  
Bayesian Model Selection Approach

scholarly journals Combining dimensions and features in similarity-based representations

2019 ◽  
Author(s):  
Danielle Navarro ◽  
Michael David Lee
Keyword(s):  
Model Selection ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Data Set ◽  
Similarity Data ◽  
Model Selection Approach ◽  
Selection Approach ◽  
Representational Model ◽  
Bayesian Model Selection Approach

This paper develops a new representational model of similarity data that combines continuous dimensions with discrete features. An algorithm capable of learning these representations is described, and a Bayesian model selection approach for choosing the appropriate number of dimensions and features is developed. The approach is demonstrated on a classic data set that considers the similarities between the numbers 0 through 9.

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