Transcriptional Regulatory Circuits: Predicting Numbers from Alphabets

被引：131

作者：

Kim, Harold D. ^{[3
,4
,5
]}

Shay, Tal ^{[1
,2
]}

O'Shea, Erin K. ^{[3
,4
,5
]}

Regev, Aviv ^{[1
,2
]}

机构：

[1] MIT, Dept Biol, Cambridge, MA 02142 USA

[2] Broad Inst MIT & Harvard, Cambridge, MA 02142 USA

[3] Harvard Univ, Fac Arts & Sci, Ctr Syst Biol, Dept Mol & Cellular Biol,Howard Hughes Med Inst, Cambridge, MA 02138 USA

[4] Harvard Univ, Fac Arts & Sci, Ctr Syst Biol, Dept Chem,Howard Hughes Med Inst, Cambridge, MA 02138 USA

[5] Harvard Univ, Fac Arts & Sci, Ctr Syst Biol, Dept Biol Chem,Howard Hughes Med Inst, Cambridge, MA 02138 USA

来源：

SCIENCE | 2009年 / 325卷 / 5939期

关键词：

COMBINATORIAL CIS-REGULATION; GENE-EXPRESSION; NETWORKS; YEAST; SEQUENCE; EVOLUTION; LESSONS; MODULES; LOGIC; NOISE;

D O I：

10.1126/science.1171347

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Transcriptional regulatory circuits govern how cis and trans factors transform signals into messenger RNA (mRNA) expression levels. With advances in quantitative and high-throughput technologies that allow measurement of gene expression state in different conditions, data that can be used to build and test models of transcriptional regulation is being generated at a rapid pace. Here, we review experimental and computational methods used to derive detailed quantitative circuit models on a small scale and cruder, genome-wide models on a large scale. We discuss the potential of combining small- and large-scale approaches to understand the working and wiring of transcriptional regulatory circuits.

引用

页码：429 / 432

页数：4

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