%0 Journal Article
%T Missing Value Estimation for Microarray Expression Data based on Total Least Squares<br>基于总体最小二乘方法的基因表达缺失数据估计
%A QIU Lang-bo
%A WANG Gang
%A WANG Zheng-zhi
%A <br>邱浪波
%A 王刚
%A 王正志
%J 生物物理学报
%D 2005
%I 
%X 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.
%K Microarray expression
%K Total least squares
%K Missing value<br>基因芯片表达
%K 缺失值
%K 总体最小二乘估计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=E0C9D9BBED813D6674AC13E942EAC86D&aid=284456AAAE8EDB73&yid=2DD7160C83D0ACED&vid=659D3B06EBF534A7&iid=B31275AF3241DB2D&sid=F10601728A1E9BEA&eid=389DA78D878702A9&journal_id=1000-6737&journal_name=生物物理学报&referenced_num=1&reference_num=15