利用基因表达谱挖掘差异表达功能类的稳健性

Robustness of mining the differentially expressed functional classes based on gene expression profiles

Gene Ontology广泛地应用于基于基因芯片数据的差异表达功能类分析。基因芯片技术存在检测缺失与检测误差等问题。本文探讨上述这二个因素对利用基因表达谱挖掘Gene Ontology中差异表达功能类的影响。结果显示,差异表达功能类对于检测缺失与检测误差干扰等有一定的稳健性。

Gene Ontology is widely applied to mine differentially expressed functional classes based on the microarray experiments. However, there still are many problems of microarray technology, such as the incomplete coverage of measured genes over genome and measurement noise. We explore how such problems will affect on the mining outcomes. The results suggest that the discovered differentially expressed functional classes are robust to the factors of incomplete coverage and measurement noise.