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Biochemical complexity drives log-normal variation in genetic expression
被引:51
作者
:
Beal, Jacob
论文数:
0
引用数:
0
h-index:
0
机构:
Raytheon BBN Technologies, Cambridge,MA,02138, United States
Raytheon BBN Technologies, Cambridge,MA,02138, United States
Beal, Jacob
[
1
]
机构
:
[1]
Raytheon BBN Technologies, Cambridge,MA,02138, United States
来源
:
Engineering Biology
|
2017年
/ 1卷
/ 01期
关键词
:
Stochastic models - Stochastic systems - Digital storage - Normal distribution;
D O I
:
10.1049/enb.2017.0004
中图分类号
:
学科分类号
:
摘要
:
Cells exhibit a high degree of variation in levels of gene expression, even within otherwise homogeneous populations. The standard model to describe this variation centres on a gamma distribution driven by stochastic bursts of translation. Stochastic bursting, however, cannot account for the well-established behaviour of strong transcriptional repressors. Instead, it can be shown that the very complexity of the biochemical processes involved in gene expression drives an emergent log-normal distribution of expression levels. Emergent log-normal distributions can account for the observed behaviour of transcriptional repressors, are still compatible with stochastically constrained distributions, and have important implications for both analysis of gene expression data and the engineering of biological organisms. © 2017 Eng. Biol. All rights reserved.
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页码:55 / 60
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