[1]周天寿.生化反应系统的二项矩和属性因子[J].江西师范大学学报(自然科学版),2016,40(01):1-4.
　ZHOU Tianshou.The Binomial Moments and Attribute Factors for Biochemical Reaction Systems[J].Journal of Jiangxi Normal University:Natural Science Edition,2016,40(01):1-4.
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生化反应系统的二项矩和属性因子()
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《江西师范大学学报》（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2016年01期
页码:
1-4
栏目:
出版日期:
2016-01-25

文章信息/Info

Title:
The Binomial Moments and Attribute Factors for Biochemical Reaction Systems
作者:
周天寿
中山大学数学与计算科学学院,广东 广州 510275
Author(s):
ZHOU Tianshou
School of Mathematics and Computational Science,Sun Yet-Sen University,Guangzhou Guangdong 510275,China
关键词:
二项矩;  属性因子;  噪声强度;  Fano因子;  反应系统
Keywords:
binomial moment;  attribute factor;  noise intensity;  Fano factor;  reaction system
分类号:
O 242; Q 332
文献标志码:
A
摘要:
化学主方程对生化反应系统提供了一个建模框架,但它的分析与模拟一直是计算系统生物学的一个挑战.另一方面,矩封闭方法对化学主方程提供了一种逼近,但普通的矩当其阶趋于无穷时并不趋于0,因此具有局限性.这里,对概率密度函数引进二项矩,它具有2个突出的特点:1)当二项矩的阶充分大时二项矩趋于0; 2)二项矩能够方便地用来重构相应的概率密度函数.基于二项矩,进一步引进反应物种的属性因子,它比普通的统计指标(如噪声强度、Fano因子)具有某些优势.此外,还给出了用二项矩来表示噪声强度和Fano因子的显式公式,并用简单的生物例子来说明二项矩的优势与3种统计指标的特征.
Abstract:
Chemical master equations(CMEs)provide a framework for modeling of biochemical reaction systems,but its analysis and simulation are a challenge in computational systems biology.On the other hand,moment-closure methods provide approximations for CMEs but ordinary moments have shortcomings,e.g.,they do not tend to zero as their orders go to infinity.Binomial moments for a distribution are introduced,which have two remarkable features:1)binomial moments tend to zero as their orders go to infinity; 2)they can be conveniently used to reconstruction of the corresponding distribution.Based on binomial moments,it further introduces the attribution factor of a reactive species,which has more advantages than common statistical indices such as noise intensity and Fano factor.In addition,it gives explicit formulae for calculating common statistical indices,and uses simple biological examples to show advantages of binomial moments and characteristics of three statistics.

参考文献/References:

[1] Zaikin A N,Zhabotinsky A M.Concentration wave propagation in two-dimensional liquid-phase self-oscillating system [J].Nature,1970,225(5232):535-537.
[2] Thattai M,Van Oudenaarden A.Intrinsic noise in gene regulatory networks [J].Proc Natl Acad Sci U S A,2001,98(15):8614-8619.
[3] 周天寿,胡长春.三类基因振子和它们的基本动力学 [J].江西师范大学学报:自然科学版,2008,32(1):1-5.
[4] Lotka A J.Contribution to the theory of periodic reaction [J].J Phys Chem,1910,14(3):271-274.
[5] Gillespie D T.A general method for numerically simulating the stochastic time evolution of coupled chemical reactions [J].J Comput Phys,1976,22(4):403-434.
[6] Munsky B,Khammash M.The finite state projection algorithm for the solution of the chemical master equation [J].J Chem Phys,2006,124(4):044104.
[7] Ale A,Kirk P,Stumpf M P.A general moment expansion method for stochastic kinetic models [J].J Chem Phys,2013,138(17):3869-3876.
[8] Smadbeck P,Kaznessis Y N.A closure scheme for chemical master equations [J].Proc Natl Acad Sci U S A,2013,110(35):14261-14265.
[9] Zechner C,Ruess J,Krenn P,et al.Moment-based inference predicts bimodality in transient gene expression [J].Proc Natl Acad Sci U S A,2012,109(21):8340-8345.
[10] Grima R.A study of the accuracy of moment-closure approximations for stochastic chemical kinetics [J].J Chem Phys,2012,136(15):1591-1596.
[11] Balakrishnan N,Johnson N L,Kotz S.A note on relationships between moments,central moments and cumulants from multivariate distributions [J].Stat Probabil Lett,1998,39(1):49-54.
[12] He Yong,Barkai E.Super- and sub-poissonian photon statistics for single molecule spectroscopy [J].J Chem Phys,2004,122(18):184703.
[13] Friedman N,Cai Long,Xie X Sunny.Linking stochastic dynamics to population distribution:an analytical framework of gene expression [J].Phys Rev Lett,2006,97(16):168302.
[14] 周天寿.基因表达系统的研究进展:概率分布 [J].江西师范大学学报:自然科学版,2012,36(3):221-229.
[15] Zhang Jiajun,Zhou Tianshou.Promoter-mediated transcriptional dynamics [J].Biophys J,2014,106(2):479-488.
[16] Singh A,Bokes P.Consequences of mRNA transport on stochastic variability in protein levels [J].Biophys J,2012,103(5):1087-1096.
[17] Wang Qianliang,Zhou Tianshou.Dynamical analysis of mCAT2 gene models with CTN-RNA nuclear retention [J].Phys Biol,2015,12(1):016010.
[18] Zhang Jiajun,Huang Lifang,Zhou Tianshou.Comment on ‘binomial moment equations for chemical reaction networks' [J].Phys Rev Lett,2014,112(8):088901.

备注/Memo

备注/Memo:
基金项目:国家自然科学基金/重大研究计划/重点支持项目(91230204)和科技部973项目子课题(2014CB964703)资助项目.
更新日期/Last Update: 1900-01-01