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Analysis of microarray gene expression data
- Current Bioinformatics
, 2006
"... Abstract: Microarrays provide the biological research community with tremendously rich, sensitive and detailed information on gene expression profiles. Gene expression profiling and gene expression patterns have been found useful for solving a wide variety of important biological and biomedical prob ..."
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Cited by 11 (0 self)
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problems, including the study of metabolic pathways, inference of the functions of unknown genes, diagnosis of diseased states, as well as facilitating the development of individualized drug treatments through pharmacogenomics. Given the significant impact of microarray gene expression data in biological
Visualization of microarray gene expression data
"... Microarray gene expression data is used in various biological and medical investigations. Processing of gene expression data requires algorithms in data mining, process automation and knowledge discovery. Available data mining algorithms exploits various visualization techniques. Here, we describe t ..."
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Microarray gene expression data is used in various biological and medical investigations. Processing of gene expression data requires algorithms in data mining, process automation and knowledge discovery. Available data mining algorithms exploits various visualization techniques. Here, we describe
On the classification of microarray gene-expression data
, 2012
"... We consider the classification of microarray gene-expression data. First, attention is given to the supervised case, where the tissue samples are classified with respect to a number of predefined classes and the intent is to assign a new unclassified tissue to one of these classes. The problems of f ..."
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We consider the classification of microarray gene-expression data. First, attention is given to the supervised case, where the tissue samples are classified with respect to a number of predefined classes and the intent is to assign a new unclassified tissue to one of these classes. The problems
Some Statistical Issues in Microarray Gene Expression Data
- RADIAT. RES. 165, 745–748 (2006).
, 2006
"... In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three con ..."
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Cited by 1 (0 self)
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In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three
tistical Issues in Microarray Gene Expression Data. Radiat.
"... In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three con ..."
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In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three
Analysis of Microarray Gene Expression Data
- in ‘Handbook of Statistical Genetics’, 2nd edn
, 2003
"... This article reviews the methods utilized in processing and analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of mRNA abundance in a set of tissues or cell populations for thousands of genes simultaneously. Naturally, suc ..."
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Cited by 16 (1 self)
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This article reviews the methods utilized in processing and analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of mRNA abundance in a set of tissues or cell populations for thousands of genes simultaneously. Naturally
Microarray Gene Expression Data Analysis
"... Image analysis is a crucial step in processing microarray data generated by gene expression studies, which have been used extensively in understanding the molecular mechanisms of injury and recovery. A novel image analysis method utilizing an efficient snake-based multichannel image segmentation alg ..."
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Image analysis is a crucial step in processing microarray data generated by gene expression studies, which have been used extensively in understanding the molecular mechanisms of injury and recovery. A novel image analysis method utilizing an efficient snake-based multichannel image segmentation
clustering of microarray gene expression data
, 2005
"... Motivation: Cluster analysis of gene expression profiles has been widely applied to clustering genes for gene function discovery. Many approaches have been proposed. The rationale is that the genes with the same biological function or involved in the same biological process are more likely to co-exp ..."
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Motivation: Cluster analysis of gene expression profiles has been widely applied to clustering genes for gene function discovery. Many approaches have been proposed. The rationale is that the genes with the same biological function or involved in the same biological process are more likely to co-express
Support Vector Clustering of Microarray Gene Expression Data
, 2005
"... In this paper Gaussian kernel approach will be explored for microarray gene expression data using support vector clustering (SVC). SVC uses the idea of support vector machines. The data points are mapped to a high dimensional feature space with a kernel function, and a minimal enclosing sphere in lo ..."
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Cited by 1 (0 self)
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In this paper Gaussian kernel approach will be explored for microarray gene expression data using support vector clustering (SVC). SVC uses the idea of support vector machines. The data points are mapped to a high dimensional feature space with a kernel function, and a minimal enclosing sphere
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766,925
