VIII Mediterranean School of Complex NetworksCatania, Sicily 25 - 30 June 2023
Arrival at the hotel, self-organized by the attendant.
9:00 - 10:00 OPENING & Individual Presentations
Giuseppe Mangioni (University of Catania, Italy)
Alex Arenas (Universitat Rovira I Virgili, Spain)
10:00 - 10:30 COFFEE BREAK
10:30 - 12:00 SESSION I - Part I
Structure of complex networks
The omnipresence of complex networks in all kinds of disciplines, and the fact that some of their structural properties are shared by many of them, has led to an increasing interest in the study of complex network. Nowadays, network science has become an essential toolkit to analyze, model and understand any system exhibiting pairwise interactions between its components. We will explain the main structural characteristics of complex networks, the mathematical and computational tools for their analysis, and some models that help to explain the appearance of some of these characteristics.
15:30 - 17:00 SESSION I - Part II
Structure of multilayer networks
Multilayer networks are networks in which the edges can be of different types, thus forming layers. We will review the main structural features of these networks, highlighting the differences with respect to standard single-layer networks. Although it may seem that multilayer networks are particular cases of complex networks, we will show that the multilayer structure can be intrinsically different, inducing unexpected emergent behaviors that could not be predicted beforehand.
17:00 - 17:30 COFFEE BREAK
17:30 - 18:30 Student talks
- Celine Sin
- Kimberly Nestor
- Clelia Corridori
- Giulia Cesaro
- Giacomo Baruzzo
- Chiara Condorelli
- Teresa Lázaro Sánchez
9.00 - 10.30 Focused Seminars I
Modelling Financial Distress Propagation
Financial networks have been the object of intense quantitative analysis during the last decades. Their structure and the dynamical processes on top of them, are of utmost importance to understand the emergent collective behavior behind economic and financial crises. Daily business interactions form a direct and weighted customer-supplier network whose structure has in-depth implications for its functioning. A company's financial distress depends on the capacity of its clients to fulfill their payments. Otherwise, a firm cannot keep working unless it applies for a loan. Recent financial crises have prompted much new research on the interconnectedness of companies and the extent to which it contributes to systemic fragility. In this talk, we study the interplay between network complexity and market stability in a deliberately simplified model for financial distress propagation. To this aim, we introduce a stylized model to understand the domino effect of distress in client-supplier networks, providing a theoretical analysis, and applying it to several synthetic networks and a real customer-supplier network supplied by one of the largest banks in Europe. Besides, the model allows researchers to investigate possible scenarios for the functioning of the financial distress propagation and to assess the complete network's economic health. The described model is based on the combination of two stochastic terms: a) an additive noise, accounting for the capability of trading and paying obligations, and b) a multiplicative noise representing market variations. Both parameters are crucial to determining the maximum default probability and the diffusion process characteristics.
10:30 - 11:00 COFFEE BREAK
11:00 - 12:30 Student talks
- Giacomo Barzon
- Giovanni Palermo
- Louis Bremaud
- Cinzia Tomaselli
- Wei Zhang
- Christos Charalambous
- Sara Benedetti
- Hugo Pérez-Martínez
- Maarten van den Ende
- Marya Poterek
Network Medicine: Concepts, Methods, and Applications
Network Medicine applies techniques from network science to investigate disease. A range of network medicine approaches have been developed to improve the diagnosis, prognosis, and treatment of complex diseases. Modeling molecular networks by integrating multiple types of Omics data, in particular, provides a powerful way to identify disease-related biological mechanisms and dissect disease heterogeneity. Along these lines, our group has developed a suite of computational approaches that support: (1) effectively integrating multi-Omic data to model gene regulatory networks; (2) performing network analysis to identify regulatory mechanisms mediating changes in disease state; and (3) linking network alterations with patient phenotypes to support precision medicine. In this lecture series, I will provide a broad introduction to the field of Network Medicine as well as a summary of how molecular networks have been applied in biology and medicine. I will also give a detailed review of a collection of methods our group has developed for gene regulatory network reconstruction and analysis. Finally, I will discuss several specific applications in which we have used these approaches to discover new features of disease and to understand the complex regulatory processes at work across patients.
16:00 - 17:00 PART I
17:00 - 17:30 COFFEE BREAK
17:30 - 18:30 PART II
Ecological Networks, Dynamics and Ecosystem Stability
In these two lectures, I will present some classical models of ecosystems dynamics, ranging from mean field and stochastic models to multi-dimensional deterministic ones. I will show how the structure of ecological networks is fundamentally intertwined to their population dynamics. I will finally illustrate how both structure and dynamics determines the stability of ecosystems.
9:00 - 10:30 PART I
10:30 - 11:00 COFFEE BREAK
11:00 - 12:30 PART II
16:00 - 17:00 STUDENT TALKS
- Fabio Menegazzo
- Sara M. Vallejo-Bernal
- Gabriele Puglisi
- Swanand Khanapurkar
- Sara Venturini
- Zhang Zhang
- Santiago Lamata Otín
17:00 - 17:30 COFFEE BREAK
17:30 - 18:30 STUDENT TALKS
- Pau Esteve
- Lorenzo Di Meco
- Jonas Wassmer
- Tina Šfiligoj
- Bernat Salbanyà
- Alessandra Corso
20.00 - 22:00 social dinner
9.00 - 10.30 Focused Seminars II
Spatial growth of urban transportation infrastructures
Roads and subways are crucial networks that constitute in some sort the backbone of a city. These networks evolve in time and space and usually co-evolve with cities, so that their understanding is critical for constructing a science of cities. In this lecture, after a general introduction about urban networks, I will discuss the evolution of street networks and subways in large cities. I will introduce the main tools for measuring their salient properties, discuss the main features of their growth and discuss some models for these systems, as well as some challenges for future research.
10.30 - 11.00 COFFEE BREAK
11.00 - 12:30 PROJECTS TIME
15.00 - 22.00 Etna Volcano Tour
9.00 - 10.30 Focused Seminars III
Community detection is an important problem that consists on grasping the intrinsic topological structures of networked data, without any previous knowledge about the size or number of groups to be found. This is of utmost importance in exploratory data analysis, specially in experimental fields like biology, chemistry, and many others. The main difficulty that scientists face when trying to do community analysis relies on finding the appropriate definitions and algorithms for each problem at hand. Nowadays, a myriad of methods are available, and some are even embedded in network analysis tools, making it easy for scientists to apply the most popular community algorithm right away, but also hiding the whole community detection process in a black box. In this lecture we will review community detection from its very definition, considering the advantages and drawbacks of the most popular approaches, in hopes to build a grounded knowledge about this problem so that every scientist is able to critically choose the appropriate solution for his problem.
10.30 - 11.00 COFFEE BREAK
11.00 - 12:30 Focused Seminars IV
THE DYNAMICS OF SOCIAL SYSTEMS WITH HIGHER-ORDER INTERACTIONS
Networks are made of nodes and links. Hence, they are suited to study processes, such as the spreading of a disease in a population, in which transmission occurs through pairwise contacts. Conversely, networks cannot describe well other dynamical processes, such as the adoption of innovation or the formation of opinions in a social system, where more complex mechanisms of transmission and reinforcement are at work. In this lecture, I will discuss how to go beyond complex networks  and I will illustrate, with three different examples, how to use higher-order networks to better model social dynamics.
I will first present a higher-order model of social contagion in which a social system is represented by a simplicial complex, and the contagion can occur through interactions in groups of different sizes . I will show that higher-order interactions induce the emergence of a discontinuous phase transition in the model, with a related bistable region where healthy and endemic states co-exist. This result can help explaining why critical masses are required to initiate social changes.
I will then introduce a general framework to study collective behaviors in networks of dynamical units coupled through two-body and three-body interactions. I will show how to derive general conditions for the existence and stability of synchronization, in the form of a Master Stability Function, and I will illustrate with some case studies how higher-order interactions can help stabilizing otherwise unstable synchronized states .
inally, I will discuss a method to extend evolutionary games to higher-order networks [4,5]. Considering a system of many players involved both in pairwise and in three-player Prisoner Dilemmas, described by the hyperedges of a hypergraphs with tunable structure, I will show that, when the fraction of three-player games is larger than a certain threshold, the dynamics shows an explosive transition to a bistable state where, besides full defection, a cooperative stable state emerges.
16.00 - 17.00 Projects presentation
17.00 - 17.30 COFFEE BREAK
17.30 - 18:30 Award & closing cerimonies
|1||KIMBERLY GLASS (Harvard University, USA)||MARC BARTHELEMY (Institut de Physique Theorique in Saclay, France)||Alex Arenas (Universitat Rovira i Virgili, Spain)|
|2||SERGIO GOMEZ (Universitat Rovira i Virgili, Spain)||Clara Granell (Universitat Rovira i Virgili, Spain)||Vincenza Carchiolo (University of Catania, Italy)|
|3||SAMIR SUWEIS (University of Padua, Italy)||VITO LATORA (University of Catania and QMUL, Italy and UK)||Manlio De Domenico (University of Padua, Italy)|
|4||JORDI NIN (ESADE, Spain)||Mattia Frasca (University of Catania, Italy)|
|5||Giuseppe Mangioni (University of Catania, Italy)|
|9||Grassia Marco (University of Catania, Italy)|