Marcello Delitala – författare

This book develops methods using mathematical kinetic theory to describe the evolution of several socio-biological systems. Specifically, it deals with modeling and simulations of biological systems constituted by large populations of interacting cells, whose dynamics follow both the rules of mechanics as well as their own ability to organize movement and biological functions. Proposed is a new biological model focused on the analysis of competition between cells of an aggressive host and cells of the immune system. Modeling in kinetic theory may represent a way to understand phenomena of nonequilibrium statistical mechanics that is not described by the traditional macroscopic approach. The authors of this work focus on models that refer to the Boltzmann equation (generalized Boltzmann models) with the dynamics of populations of several interacting individuals (kinetic population models). The book follows the classical research line applied to modeling real systems, linking the phenomenological observation of systems to modeling and simulations. Computational algorithms are applied and qualitative analysis techniques are used to identify the prediction ability of specific models.The book will be a valuable resource for applied mathematicians as well as researchers in the field of biological sciences. It may also be used for advanced graduate courses in biological systems modeling with applications to collective social behavior, immunology, and epidemiology.

ContentsandScienti?cAims The scienti?c community is aware that the great scienti?c revolution of this century will be the mathematical formalization, by methods of applied mathematics, of complex biological systems. A fascinating prospect is that biological sciences will ?nally be supported by rigorous investigation me- ods and tools, similar to what happened in the past two centuries in the case of mechanical and physical sciences. It is not an easy task, considering that new mathematical methods maybeneededtodealwiththeinnercomplexityofbiologicalsystemswhich exhibit features and behaviors very di?erent from those of inert matter. Microscopic entities in biology, say cells in a multicellular system, are characterized by biological functions and the ability to organize their dynamics and interactions with other cells. Indeed, cells organize their dynamics according to the above functions, while classical particles follow deterministic laws of Newtonian mechanics. Cells have a life according to a cell cycle which ends up with a programmed death. The dialogue among cells can modify their behavior. The activity of cells includes proliferation and/or destructive events which may, in some cases, result in dangerously reproductive events. Finally, a cellular system may move far from eq- librium in physical situations where classical particles generally show a tendency toward equilibrium. An additional source of complexity is that biological systems always need a multiscale approach. Speci?cally, the dynamics of a cell, including its life, are ruled by sub-cellular entities, while most of the phenomena can be e?ectively observed only at the macroscopic scale.

”Managing Complexity, Reducing Perplexity” is devoted to an overview of the status of the art in the study of complex systems, with particular focus on the analysis of systems pertaining to living matter. Both senior scientists and young researchers from diverse and prestigious institutions with a deliberately interdisciplinary cut were invited, in order to compare approaches and problems from different disciplines. The common aim of the contributions was to analyze the complexity of living systems by means of new mathematical paradigms that are more adherent to reality and which are able to generate both exploratory and predictive models that are capable of achieving a deeper insight into life science phenomena.

”Managing Complexity, Reducing Perplexity” is devoted to an overview of the status of the art in the study of complex systems, with particular focus on the analysis of systems pertaining to living matter. Both senior scientists and young researchers from diverse and prestigious institutions with a deliberately interdisciplinary cut were invited, in order to compare approaches and problems from different disciplines. The common aim of the contributions was to analyze the complexity of living systems by means of new mathematical paradigms that are more adherent to reality and which are able to generate both exploratory and predictive models that are capable of achieving a deeper insight into life science phenomena.