PROBLEMS IN MODELING AND PROGNOSING OF COMPLEX BIOLOGICAL SYSTEMS (COMPLEXITY)
The contradictions of modern science in relation to complex biological systems complexity -complexity have been represented. The most important of these - absence of arbitrary repetition of the initial state x(t<sub>0</sub>) of complex system, their development trajectories x(t) and final state x(t<sub>k</sub>). The lack of repetitions makes it impossible to forecast the future state of biological systems. Even in the framework of dynamic chaos, we must require that the possibility of repetition of the initial state x(t<sub>0</sub>) for biosystems, and the final state in the form of Lorenz attractor is also a definite. It is connected with invariant measures and convergence of autocorrelation functions A(t) to zero, but this is not observed for complex biological systems. It’s been presented another mathematical approach in the form of chaos-self-organization theory and other research methods based on new concepts of rest and motion, on a new concept of homeostasis and evolution, a new understanding of dynamics of living systems. Their further study within the framework of determinism (i.e. functional analysis), stochastics or dynamic chaos, becomes completely useless. These are unique systems and they are not the subject of modern science. I.R. Prigogine talked about this. But Prigogine didn’t go beyond the stochastics in the study of complexity (or emergent systems by J.A. Wheeler).