Towards predictive stochastic dynamical modeling of cancer genesis and progression

  • P. AoEmail author
  • D. Galas
  • L. Hood
  • L. Yin
  • X. M. Zhu


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.

Key words

cancer stochastic processes systems biology endogenous network functional landscape 


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Copyright information

© International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine of Ministry of EducationShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Departments of Mechanical Engineering and PhysicsUniversity of WashingtonSeattleUSA
  3. 3.Institute for Systems BiologySeattleUSA
  4. 4.School of PhysicsPeking UniversityBeijingChina
  5. 5.GenMath, Corp.SeattleUSA

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