Clustering of Time-Course Microarray Data Using Pharmacokinetic Parameter

被引：0
|
作者：
Lee, Hyo-Jung [1 ]
Kim, Peol-A [2 ]
Park, Mira [3 ]
机构：
[1] Korea Univ, Dept Stat, Seoul, South Korea
[2] KFDA, Pharmaceut & Med Devices Res Dept, Seoul, South Korea
[3] Eulji Univ, Dept Prevent Med, Daejeon 301832, South Korea
来源：
KOREAN JOURNAL OF APPLIED STATISTICS | 2011年 / 24卷 / 04期
基金：
新加坡国家研究基金会;
关键词：
Time-course microarray data; pharmacokinetic parameter; clustering;
D O I：
10.5351/KJAS.2011.24.4.623
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
A major goal of time-course microarray data analysis is the detection of groups of genes that manifest similar expression patterns over time. The corresponding numerous cluster algorithms for clustering time-course microarray data have been developed. In this study, we proposed a clustering method based on the primary pharmacokinetic parameters in the pharmacokinetics study for assessment of pharmaceutical equivalents between two drug products. A real data and a simulation data was used to demonstrate the usefulness of the proposed method.
引用
收藏
页码：623 / 631
页数：9
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