Mixed models have typically been used for modelling structural effects in presence of random variations. These type of models can be used rather naturally when we work with microarray data. In this paper, we shall look at two extensions of the usual mixed effect models
The main goal in analyzing microarray data is to determine the genes that are differentially express...
Several statistical methods are nowadays available for the analysis of gene expression data recorded...
Several statistical methods are nowadays available for the analysis of gene expression data recorded...
Mixed models have typically been used for modelling structural effects in presence of random variati...
This research mainly focused on statistical tools and software for the analysis of microarray data. ...
The microarray is an important and powerful tool for prescreening of genes for further research. How...
International audienceData variability can be important in microarray data analysis. Thus, when clus...
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
- ii-Microarray technology enables researchers to simultaneously monitor the expression levels of th...
An important goal of microarray studies is the detection of genes that show significant changes in o...
The analysis of microarray data remains a challenge as one wish to investigate the possibility of th...
International audienceExperimental techniques in biology such as microfluidic devices and time-lapse...
This project captures the problem of large microarray datasets and seeks to identify a statistical m...
International audienceExperimental techniques in biology such as microfluidic devices and time-lapse...
International audienceExperimental techniques in biology such as microfluidic devices and time-lapse...
The main goal in analyzing microarray data is to determine the genes that are differentially express...
Several statistical methods are nowadays available for the analysis of gene expression data recorded...
Several statistical methods are nowadays available for the analysis of gene expression data recorded...
Mixed models have typically been used for modelling structural effects in presence of random variati...
This research mainly focused on statistical tools and software for the analysis of microarray data. ...
The microarray is an important and powerful tool for prescreening of genes for further research. How...
International audienceData variability can be important in microarray data analysis. Thus, when clus...
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
- ii-Microarray technology enables researchers to simultaneously monitor the expression levels of th...
An important goal of microarray studies is the detection of genes that show significant changes in o...
The analysis of microarray data remains a challenge as one wish to investigate the possibility of th...
International audienceExperimental techniques in biology such as microfluidic devices and time-lapse...
This project captures the problem of large microarray datasets and seeks to identify a statistical m...
International audienceExperimental techniques in biology such as microfluidic devices and time-lapse...
International audienceExperimental techniques in biology such as microfluidic devices and time-lapse...
The main goal in analyzing microarray data is to determine the genes that are differentially express...
Several statistical methods are nowadays available for the analysis of gene expression data recorded...
Several statistical methods are nowadays available for the analysis of gene expression data recorded...