| Contents |
| The classical theory evolution of biological systems and populations is
based on that robust and distinct, functional equlibria are selected for.
Even the transition to the equilibria was supposed to be based on the so
called minimum frustration principle and funneling landscape. The noise in these models are
included in a thermodynamic, funneling landscape model for molecular folding/binding
and an analogous landscape in (cell) populations.
Recent research both on the molecular level, signalling/decision level of single cell and on the (cell) population level
indicates that these landscape models are not necessarily minimal frustrated, but
that quasistationary states modulated by noise change the properties of the
biological system. One of the most popular approaches to include noise
modulation are through bayesian prior statistics of the noise variance
(superstatistics) which can be specialized to the Tsallis statistics.
We formulate a two scale protein landscape model for protein
folding which includes stochastics variations in the contact number both at
a short range scale and a long range scale. We show that this lead to
an interesting model for a nonextensive mean free energy difference which
gives a possible bridge between ordered and disordered protein folding. Both
a dynamic Langevin type model with multiplicative contact number noise
and long range interactions modelled by a bayesian prior model are
discussed. Consequences for the protein folding landscape in terms of
nonextensive folding rates and stability are discussed. The
evolutionary theory of stem cell decision rates is also discussed together with
possible consequences for diseases. |
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