Gene Expression Analysis with Data Mining.
نویسندگان
چکیده
منابع مشابه
Microarray Gene Expression Data Mining with Cluster Analysis using GeneSightTM
After the sequencing of the human genome recently, efforts have been directed towards the annotation of sequenced genes. The functional identity of the genes and the elucidation of their participation in various biological pathway(s) is the prime focus of laboratory research and informatics efforts in this post-genomics era. Since many functionally related genes are co-expressed and coexpressio...
متن کاملMining Gene Expression Data
Micro-array data has enabled us to obtain an overview of the cell by measuring the expression levels of thousands of genes simultaneously. It has also opened the possibility for predicting possible cancerous cells accurately. Since these data sets are very large, we need to utilize machine learning techniques to analyse them efficiently. However, micro-array data also poses challenging problems...
متن کاملMining Microarray Gene Expression Data
DNA microarray technology provides biologists with the ability to measure the expression levels of thousands of genes in a single experiment. Many initial experiments suggest that genes of similar function yield similar expression patterns in microarray hybridization experiments. Hence it makes possible to distinguish genes with different functions by analyzing gene data generated from microarr...
متن کاملSemantic Mining and Analysis of Gene Expression Data
Association rules can reveal biological relevant relationship between genes and environments / categories. However, most existing association rule mining algorithms are rendered impractical on gene expression data, which typically contains thousands or tens of thousands of columns (gene expression levels), but only tens of rows (samples). The main problem is that these algorithms have an expone...
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ژورنال
عنوان ژورنال: Seibutsu Butsuri
سال: 2001
ISSN: 0582-4052,1347-4219
DOI: 10.2142/biophys.41.132