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
相关论文
共 50 条
  • [21] Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference
    Peddada, SD
    Lobenhofer, EK
    Li, LP
    Afshari, CA
    Weinberg, CR
    Umbach, DM
    [J]. BIOINFORMATICS, 2003, 19 (07) : 834 - 841
  • [22] Novel technique for preprocessing high dimensional time-course data from DNA microarray: mathematical model-based clustering
    Hakamada, K
    Okamoto, M
    Hanai, T
    [J]. BIOINFORMATICS, 2006, 22 (07) : 843 - 848
  • [23] Identifying Differentially Expressed Genes for Time-course Microarray Data through Functional Data Analysis
    Chen K.
    Wang J.-L.
    [J]. Statistics in Biosciences, 2010, 2 (2) : 95 - 119
  • [24] Inference of dynamic networks using time-course data
    Kim, Yongsoo
    Han, Seungmin
    Choi, Seungjin
    Hwang, Daehee
    [J]. BRIEFINGS IN BIOINFORMATICS, 2014, 15 (02) : 212 - 228
  • [25] Robust test method for time-course microarray experiments
    Sohn, Insuk
    Owzar, Kouros
    George, Stephen L.
    Kim, Sujong
    Jung, Sin-Ho
    [J]. BMC BIOINFORMATICS, 2010, 11
  • [26] Robust test method for time-course microarray experiments
    Insuk Sohn
    Kouros Owzar
    Stephen L George
    Sujong Kim
    Sin-Ho Jung
    [J]. BMC Bioinformatics, 11
  • [27] A recursively partitioned mixture model for clustering time-course gene expression data
    Koestler, Devin C.
    Marsit, Carmen J.
    Christensen, Brock C.
    Kelsey, Karl T.
    Houseman, E. Andres
    [J]. TRANSLATIONAL CANCER RESEARCH, 2014, 3 (03) : 217 - +
  • [28] Friendly neighbors method for unsupervised determination of gene significance in time-course microarray data
    Murthy, KRK
    Vega, VB
    [J]. BIBE 2004: FOURTH IEEE SYMPOSIUM ON BIOINFORMATICS AND BIOENGINEERING, PROCEEDINGS, 2004, : 351 - 357
  • [29] BAYESIAN CLUSTERING OF REPLICATED TIME-COURSE GENE EXPRESSION DATA WITH WEAK SIGNALS
    Fu, Audrey Qiuyan
    Russell, Steven
    Bray, Sarah J.
    Tavare, Simon
    [J]. ANNALS OF APPLIED STATISTICS, 2013, 7 (03): : 1334 - 1361
  • [30] Quality-Based Clustering of Functional Data: Applications to Time Course Microarray Data
    Scharl, Theresa
    Leisch, Friedrich
    [J]. ADVANCES IN DATA ANALYSIS, DATA HANDLING AND BUSINESS INTELLIGENCE, 2010, : 675 - +
12345