6. Biophysics

Workshop organized by: P. Paradisi

Applying Complexity Science in Biology and Medicine

In recent years an increasing interest is being devoted to the application of ideas, concepts and tools from the socalled “complexity science” to biological systems. Living matter represents a prototype of complex systems, as a possible definition of complexity includes the following features:

• many individual units having strong non-linear interactions (complex networks, neural systems, cell signalling);

• emergence of cooperative behaviour and self-organization;

• self-organized structures are not final equilibrium states, but metastable states;

• transitions among states is typically associated with a non-Poisson intermittent behaviour;

• systems are “pumped” with external energy supply;

• beyond homeostasis: time periods with low entropy increase rate and also periods with local decrease of entropy (optimal interaction with the external environment);

• the system is far from equilibrium, but is stationary or quasi-stationary if environmental conditions are stationary;

• non-reducibility: the emergent properties cannot be explained only in terms of the single components (like in critical phenomena, “the whole is more than the sum of the parts”). In this special session or workshop we encourage the submission of works concerning the investigation, either theoretical, methodological, or experimental, of complexity features in biology and biomedicine. Methods may include (but are not limited to): multi-scale modelling; scaling-relations analyses, fractals and multifractals, long-range memory, critical phenomena, Self-Organized Criticality (SOC), extended criticality, stochastic/dynamical models, non-linear systems, complex networks, non-extensive entropy. Examples of applications are expected within and across the following different levels:

• Single cell level, e.g. gene expression, protein-protein interaction, metabolic networks;

• Multi-cellular level, e.g. cell-cell interaction, tissues, in vitro neural networks;

• Multi-cellular living organisms, including physiology, e.g. brain physiology, autonomic system, mind-body interaction, brain-heart axis;

• Organisms in interaction, both mutual (e. g. swarm intelligence, eukaryotes and prokaryiotes emerging properties in vitro and in vivo) and/or with their environment (e. g. foraging strategies).