Statistical challenges in functional genomics

被引:69
作者
Sebastiani, P [1 ]
Gussoni, E
Kohane, IS
Ramoni, MF
机构
[1] Univ Massachusetts, Dept Math & Stat, Amherst, MA 01003 USA
[2] Harvard Univ, Childrens Hosp, Sch Med, Dept Med, Boston, MA 02115 USA
[3] Harvard Univ, Childrens Hosp, Sch Med, Informat Program, Boston, MA 02115 USA
关键词
bioinformatics; classification; clustering; differential analysis; gene expression; functional genomics; microarray;
D O I
10.1214/ss/1056397486
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
On February 12, 2001 the Human Genome Project announced the completion of a draft physical map of the human genome-the genetic blueprint for a human being. Now the challenge is to annotate this map by understanding the functions of genes and their interplay with proteins and the environment to create complex, dynamic living systems. This is the goal of functional genomics. Recent technological advances enable biomedical investigators to observe the genome of entire organisms in action by simultaneously measuring the level of activation of thousands of genes under the same experimental conditions. This technology, known as microarrays, today provides unparalleled discovery opportunities and is reshaping biomedical sciences. One of the main aspects of this revolution is the introduction of computationally intensive data analysis methods in biomedical research. This article reviews the foundations of this technology and describes the statistical challenges posed by the analysis of microarray data.
引用
收藏
页码:33 / 60
页数:28
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