GENE_EXPRESSION_DATA

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Challenges Analyzing RNA-Seq Gene Expression Data
《Open Journal of Statistics》2016年第4期628-636,共9页Liliana López-Kleine Cristian González-Prieto 
The analysis of messenger Ribonucleic acid obtained through sequencing techniques (RNA-se- quencing) data is very challenging. Once technical difficulties have been sorted, an important choice has to be made during pr...
关键词:RNA-Seq Analysis Count Data PREPROCESSING Differential Expression Gene Co-Expression Network 
Application of Sparse Bayesian Generalized Linear Model to Gene Expression Data for Classification of Prostate Cancer Subtypes被引量:2
《Open Journal of Statistics》2014年第7期518-526,共9页Behrouz Madahian Lih Y. Deng Ramin Homayouni 
A major limitation of expression profiling is caused by the large number of variables assessed compared to relatively small sample sizes. In this study, we developed a multinomial Probit Bayesian model which utilizes ...
关键词:LASSO ROBUSTNESS SPARSITY MCMC Gibbs Sampling 
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