Complex Systems Biology (CSB) is a new discipline devoted to the characterization of biological systems by means of the methods and the instruments provided by the Science of Complex Systems. CSB differs from Systems Biology because the main focus is on the search, the description and the comprehension of those properties that can be defined generic or universal, rather than on the description and classification of specific systems. Those properties, among which self-organization, robustness, evolvibility, heredity and diversity, are defined generic since they are common to a wide range of biological systems and, in some cases, to living beings in general. Since biological organisms are integrated highly hierarchical systems the holistic and systems approach of CSB turns out to be deeply effective and complementary to the reductionist methodology typical of Molecular Biology.

Biological systems are characterized by a large number of interacting constituents (e.g. nucleic acid, proteins, low weight organic compounds, etc.). Accordingly, biological systems can be described and understood within the framework of a high dimensional phase space, by means of sophisticated mathematical modelling and advanced statistical methodologies, in order to describe the emergence of proprieties not deducible a priori, through the investigation of the individual parts of the system or their interactions only.

At ECLT we pursue biological system modelling exploiting stochastic and deterministic models. As a prerogative, the ECLT’s CBS group develops abstract models in close cooperation with experimental biologists in order to catch the general proprieties of systems yet retaining biological significance and coherence. The importance of the systems approach is well perceived looking at the new directions taken by different fields both in research and industry. The idea is to develop new kinds of “living technologies” in which the power of the emergent behaviours can rule the features of the process, like new drugs able to activating only in the presence of the target and able to reconfigure themselves while interacting with the system.

One of the main research topics at ECLT is that of autocatalytic networks of molecules. There are few examples of autocatalytic networks in present-day biological systems, which can be directly studied on the basis of extensive information which is available. However, if one is interested either in the problem of the origin of life or in the design of artificial protocells it is also important to study the generic properties of these systems, and the way in which they change in time under the action of mutation and selection.

Artificial protocells are also handled from the theoretical point of view. Protocells could be lipid vesicles, or micelles, endowed with some rudimentary metabolism and should contain “genetic” material, being able to grow, reproduce and evolve. While viable protocells do not exist yet, their study is important in order to understand possible scenarios for the origin of life, as well as for creating new “synthetic life” forms which are able to adapt and evolve. This endeavour has an obvious theoretical interest, but it also leads to an entirely new concept of “living technology”, definitely different from conventional biotechnology, which embodies the essential properties of life, such as self-organization, adaptability, capacity to evolve and react to environmental stimuli.

Another important research theme at ECLT is that of models of gene regulatory networks (GRN). In particular, the research activity involves the implementation, the evolution and the in-depth analysis of Boolean models of genetic networks, starting from the original model of Random Boolean Networks (RBN) developed by Stuart A. Kauffman. Particular attention is devoted to the characterization of the dynamical properties of such systems, mostly in regards to their robustness. The concept of dynamical criticality turns out to be central as well, mostly in relation to the fascinating hypothesis of biological systems laying in the dynamical critical regime, which should ensure the best trade-off between robustness and evolvibility.