Cancer Genesis and Progression as Dynamics in Functional Landscape of Endogenous Molecular-Cellular Network

Biology – Quantitative Biology – Subcellular Processes

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

13 pages

Scientific paper

An endogenous molecular-cellular network for both normal and abnormal functions is assumed to exist. This endogenous network forms a nonlinear stochastic dynamical system, with many stable attractors in its functional landscape. Normal or abnormal robust states can be decided by this network in a manner similar to the neural network. In this context cancer is hypothesized as one of its robust intrinsic states. This hypothesis implies that a nonlinear stochastic mathematical cancer model is constructible based on available experimental data and its quantitative prediction is directly testable. Within such model the genesis and progression of cancer may be viewed as stochastic transitions between different attractors. Thus it further suggests that progressions are not arbitrary. Other important issues on cancer, such as genetic vs epigenetics, double-edge effect, dormancy, are discussed in the light of present hypothesis. A different set of strategies for cancer prevention, cure, and care, is therefore suggested.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Cancer Genesis and Progression as Dynamics in Functional Landscape of Endogenous Molecular-Cellular Network does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Cancer Genesis and Progression as Dynamics in Functional Landscape of Endogenous Molecular-Cellular Network, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cancer Genesis and Progression as Dynamics in Functional Landscape of Endogenous Molecular-Cellular Network will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-469870

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.