Towards Predictive Stochastic Dynamical Modeling of Cancer Genesis and Progression

被引：25

作者：

Ao, P. ^{[1
,2
,3
]}

Galas, D. ^{[4
]}

Hood, L. ^{[4
]}

Yin, L. ^{[5
]}

Zhu, X. M. ^{[6
]}

机构：

[1] Shanghai Jiao Tong Univ, Minist Educ, Key Lab Syst Biomed, Shanghai Ctr Syst Biomed, Shanghai 200240, Peoples R China

[2] Univ Washington, Dept Mech Engn, Seattle, WA 98195 USA

[3] Univ Washington, Dept Phys, Seattle, WA 98195 USA

[4] Inst Syst Biol, Seattle, WA 98103 USA

[5] Peking Univ, Sch Phys, Beijing 100871, Peoples R China

[6] GenMath Corp, Seattle, WA 98105 USA

来源：

INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES | 2010年 / 2卷 / 02期

基金：

美国国家卫生研究院;

关键词：

cancer; stochastic processes; systems biology; endogenous network; functional landscape; LANDSCAPE; EXISTENCE; NETWORK;

D O I：

10.1007/s12539-010-0072-3

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Based on an innovative endogenous network hypothesis on cancer genesis and progression we have been working towards a quantitative cancer theory along the systems biology perspective. Here we give a brief report on our progress and illustrate that combing ideas from evolutionary and molecular biology, mathematics, engineering, and physics, such quantitative approach is feasible.

引用

页码：140 / 144

页数：5

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