Journal article Open Access

Key aspects of analyzing microarray gene-expression data

Chen, James J.


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{
  "DOI": "10.2217/14622416.8.5.473", 
  "author": [
    {
      "family": "Chen, James J."
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2007, 
        5, 
        1
      ]
    ]
  }, 
  "abstract": "One major challenge with the use of microarray technology is the analysis of massive amounts of gene-expression data for various applications. This review addresses the key aspects of the microarray gene-expression data analysis for the two most common objectives: class comparison and class prediction. Class comparison mainly aims to select which genes are differentially expressed across experimental conditions. Gene selection is separated into two steps: gene ranking and assigning a significance level. Class prediction uses expression profiling analysis to develop a prediction model for patient selection, diagnostic prediction or prognostic classification. Development of a prediction model involves two components: model building and performance assessment. It also describes two additional data analysis methods: gene-class testing and multiple ordering criteria.", 
  "title": "Key aspects of analyzing microarray gene-expression data", 
  "type": "article-journal", 
  "id": "1236433"
}
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