From neurocomputation to immunocomputation - a model and algorithm for fluctuation-induced instability and phase transition in biological systems

This paper explores bioinformatics-based modeling of immunological instabilities. We develop an algorithm for analyzing stability-instability properties of complex systems and use the developed technique to induce transitions in physical, biological, and engineering systems. As a case study, we analyze the phenomena of tumor destabilization or spontaneous biological regression of a malignant focus-lymphocyte interactive system. Using stochastic noise analysis, we model high-dimensional collective oscillations of nonlinear elements and study nonautonomous systems with oscillation-induced phase transitions between lowand high-dimensional states. The associated nonlinear immunodynamical phenomenon of nonequilibrial destabilization of a malignant tumor is analyzed in terms of Prigogine–Glansdorff stability theorem of dynamical systems theory.