Journal article Open Access

Key aspects of analyzing microarray gene-expression data

Chen, James J.

JSON-LD ( Export

  "description": "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.", 
  "license": "", 
  "creator": [
      "@type": "Person", 
      "name": "Chen, James J."
  "headline": "Key aspects of analyzing microarray gene-expression data", 
  "image": "", 
  "datePublished": "2007-05-01", 
  "url": "", 
  "@context": "", 
  "identifier": "", 
  "@id": "", 
  "@type": "ScholarlyArticle", 
  "name": "Key aspects of analyzing microarray gene-expression data"
Views 178
Downloads 165
Data volume 39.4 MB
Unique views 176
Unique downloads 158


Cite as