Missing Value Estimation for Microarray Expression Data based on Total Least Squares
基于总体最小二乘方法的基因表达缺失数据估计

There is missing value in microarray experiments and it will affect the stability and precision of the expression data analysis.Missing value estimating is a effective method in reducing the influence of missing values on the post-processing and there is no need for increasing experiment number.Consider the additive noise in the expression dataset,a new method based on Total Least Squares(TLS)is presented.Experimental results show that the novel method has better performance than the existing methods that have been employed.