This paper addresses the issue of the stability of lists of genes identified as differentially expressed in microarray experiments. The similarities be- tween gene rankings yielded by various gene selection methods performed with resampled datasets were assessed. The mean percentage of overlapping genes for two rankings varied from 10 to 90% depending on the applied gene selection method and the size of the list. The assessment of the stability of obtained gene rankings seems to be relevant in the analysis of microarray data
In microarray technology, many diverse experimental features can cause biases including RNA sources,...
Ranked gene lists are highly instable in the sense that similar measures of differential gene expres...
Abstract:- This paper presents adaptive algorithms for ranking and selecting differentially expresse...
Abstract Background The number of genes declared differentially expressed is a random variable and i...
This paper presents an empirical study that aims to explain the relationship between the number of s...
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
DNA microarrays have been used for the purpose of monitoring expression levels of thousands of genes...
BACKGROUND:Reproducibility is a fundamental requirement in scientific experiments. Some recent publi...
In microarray data, gene selection can make data analysis efficient and biological interpretations o...
In microarray experiments, the goal is often to examine many genes, and select some of them for addi...
A big problem in applying DNA microarrays for classification is dimension of the dataset. Recently w...
A great deal of recent research has focused on the challenging task of selecting differentially expr...
Abstract Background Microarray technology is commonly used as a simple screening tool with a focus o...
A great deal of recent research has focused on the challenging task of selecting differentially expr...
In response to the rapid development of DNA Microarray Technologies, many differentially expressed g...
In microarray technology, many diverse experimental features can cause biases including RNA sources,...
Ranked gene lists are highly instable in the sense that similar measures of differential gene expres...
Abstract:- This paper presents adaptive algorithms for ranking and selecting differentially expresse...
Abstract Background The number of genes declared differentially expressed is a random variable and i...
This paper presents an empirical study that aims to explain the relationship between the number of s...
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
DNA microarrays have been used for the purpose of monitoring expression levels of thousands of genes...
BACKGROUND:Reproducibility is a fundamental requirement in scientific experiments. Some recent publi...
In microarray data, gene selection can make data analysis efficient and biological interpretations o...
In microarray experiments, the goal is often to examine many genes, and select some of them for addi...
A big problem in applying DNA microarrays for classification is dimension of the dataset. Recently w...
A great deal of recent research has focused on the challenging task of selecting differentially expr...
Abstract Background Microarray technology is commonly used as a simple screening tool with a focus o...
A great deal of recent research has focused on the challenging task of selecting differentially expr...
In response to the rapid development of DNA Microarray Technologies, many differentially expressed g...
In microarray technology, many diverse experimental features can cause biases including RNA sources,...
Ranked gene lists are highly instable in the sense that similar measures of differential gene expres...
Abstract:- This paper presents adaptive algorithms for ranking and selecting differentially expresse...