Towards predictive stochastic dynamical modeling of cancer genesis and progression

Interdiscip Sci. 2010 Jun;2(2):140-4. doi: 10.1007/s12539-010-0072-3. Epub 2010 May 1.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Computer Simulation
  • Disease Progression
  • Evolution, Molecular
  • Humans
  • Information Theory
  • Male
  • Models, Theoretical
  • Neoplasms / metabolism*
  • Neoplasms / pathology*
  • Nonlinear Dynamics
  • Prostatic Neoplasms / pathology
  • Stochastic Processes
  • Systems Biology