Publication date
January 2005
DOIAbstract
doi:10.1093/bioinformatics/bti422 Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression dat
doi:10.1093/bioinformatics/bti422 Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression dat
With the advancement of high-throughput technologies, nowadays high-dimensional genomic and proteomi...
High-dimensional data has become a major research area in the field of genetics, bioinformatics and ...
An important application of microarray technology is to predict various clinical phenotypes based on...
Logistic regression for disease classification using microarray data: model selection in a large p a...
Global gene expression analysis using microarrays and, more recently, RNA-seq, has al-lowed investig...
An important application of microarray technology is to relate gene expression profiles to various c...
Statistical assessment of functional categories of genes deregulated in pathological conditions by u...
Exploiting sample variability to enhance multivariate analysis of microarray dat
Classification based upon gene expression data: bias and precision of error rate
One important aspect of data-mining of microarray data is to discover the molecular variation among ...
Microarray experiments have been used to investigate the relationship between gene expression and su...
New challenges within statistical sciences have arisen with the explosive growth of information. Cla...
Differential gene expression detection and sample classification using penalized linear regression m...
Quick calculation for sample size while controlling false discovery rate with application to microar...
With advances in high-density DNA microarray technology, gene expression profiling is extensively us...
With the advancement of high-throughput technologies, nowadays high-dimensional genomic and proteomi...
High-dimensional data has become a major research area in the field of genetics, bioinformatics and ...
An important application of microarray technology is to predict various clinical phenotypes based on...
Logistic regression for disease classification using microarray data: model selection in a large p a...
Global gene expression analysis using microarrays and, more recently, RNA-seq, has al-lowed investig...
An important application of microarray technology is to relate gene expression profiles to various c...
Statistical assessment of functional categories of genes deregulated in pathological conditions by u...
Exploiting sample variability to enhance multivariate analysis of microarray dat
Classification based upon gene expression data: bias and precision of error rate
One important aspect of data-mining of microarray data is to discover the molecular variation among ...
Microarray experiments have been used to investigate the relationship between gene expression and su...
New challenges within statistical sciences have arisen with the explosive growth of information. Cla...
Differential gene expression detection and sample classification using penalized linear regression m...
Quick calculation for sample size while controlling false discovery rate with application to microar...
With advances in high-density DNA microarray technology, gene expression profiling is extensively us...
With the advancement of high-throughput technologies, nowadays high-dimensional genomic and proteomi...
High-dimensional data has become a major research area in the field of genetics, bioinformatics and ...
An important application of microarray technology is to predict various clinical phenotypes based on...
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