How does noise propagate in genetic networks? A new approach to understand stochasticity in genetic networks

被引：0

作者：

Kobayashi, T ^{[1
]}

Aihara, K ^{[1
]}

机构：

[1] Univ Tokyo, Bunkyo Ku, Tokyo 1138656, Japan

来源：

CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

The emergence of apparently deterministic and reproducible behaviors from highly fluctuating components in genetic networks has been attracting great attentions. However, only little has been known on the mechanisms of such emergence because of the complexity and the digital nature in genetic networks, which make it hard and untractable to analyze them by usual dynamical and stochastic methods. In this work, we propose a new method that employs a numerical evaluation of cumulants and a graphical representation. This method visually describes propagations of fluctuations in genetic networks and facilitates intuitive understanding of stochastic properties of the networks. In addition, this method works well even if the networks consist of many components and reactions and the copy numbers of some components are low.

引用

页码：1018 / 1025

页数：8

共 50 条

[31] The Genetic Approach for Design of Virtual Private Networks
Kotenko, Igor
Saenko, Igor
2015 IEEE 18TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE), 2015, : 168 - 175
[32] A Markovian approach to the control of genetic regulatory networks
Chen, Peter C. Y.
Chen, Jeremy W.
BIOSYSTEMS, 2007, 90 (02) : 535 - 545
[33] A multiple regression approach for building genetic networks
Zhang, Shu-Qin
Ching, Wai-Ki
Tsing, Nam-Kiu
Leung, Ho-Yin
Guo, Diane D.
BMEI 2008: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOL 1, 2008, : 18 - +
[34] How social and genetic factors predict friendship networks
Boardman, Jason D.
Domingue, Benjamin W.
Fletcher, Jason M.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 109 (43) : 17377 - 17381
[35] Genetic Programming with Genetic Regulatory Networks
Lopes, Rui L.
Costa, Ernesto
GECCO'13: PROCEEDINGS OF THE 2013 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2013, : 965 - 972
[36] A new genetic approach to universal rule generation from trained neural networks
Fukumi, M
Mitsukura, Y
Akamatsu, N
IEEE 2000 TENCON PROCEEDINGS, VOLS I-III: INTELLIGENT SYSTEMS AND TECHNOLOGIES FOR THE NEW MILLENNIUM, 2000, : 1 - 6
[37] A new approach to fault diagnosis in electrical distribution networks using a genetic algorithm
Wen, FS
Chang, CS
ARTIFICIAL INTELLIGENCE IN ENGINEERING, 1998, 12 (1-2): : 69 - 80
[38] Stochastic resonance in genetic regulatory networks under Levy noise
Ding, Yamin
Shen, Jianwei
Lu, Jianquan
Kurths, Jurgen
EPL, 2019, 127 (05)
[39] A method for estimating stochastic noise in large genetic regulatory networks
Orrell, D
Ramsey, S
de Atauri, P
Bolouri, H
BIOINFORMATICS, 2005, 21 (02) : 208 - 217
[40] Exponential sensitivity of noise-driven switching in genetic networks
Mehta, Pankaj
Mukhopadhyay, Ranjan
Wingreen, Ned S.
PHYSICAL BIOLOGY, 2008, 5 (02)

← 1 2 3 4 5 →