The problem of feature gene selection and tumor samples classification of microarray gene expression data is one of challenges of gene microarray technology.
基因表达数据的特征基因选取和肿瘤样本分类问题是基因微阵列技术的挑战性课题之一。
With the extensive applications of DNA microarray technology, huge amounts of gene expression data have been generated.
随着基因芯片技术的广泛应用，产生了海量的基因表达数据。
Several classification methods based on DNA gene expression microarray data are introduced in this paper.
介绍了目前几种基于DNA微阵列基因表达数据的分类方法。
The essential and initial problem of gene expression microarray data analysis is to identify differentially expressed genes (DEGs), under certain conditions.
特定条件下的差异表达基因筛选是科学家使用芯片的初衷，也是芯片数据分析中很重要的一种应用。
Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns.
微阵列实验的全基因组基因表达模式的数据提供了前所未有的数量。
Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns.
微阵列实验的全基因组基因表达模式的数据提供了前所未有的数量。
应用推荐