1st Annual Meeting of the Padua Center for Network Medicine

From cells to societies

The Padua Center for Network Medicine (PCNM) is a distinguished research center that brings together various research laboratories within a unified and interdisciplinary effort. At the University of Padua, research laboratories from departments such as Molecular Medicine, Medicine, Biomedical Sciences, Neuroscience, Information Engineering and Physics collaborate to investigate different facets of human life and disease. These laboratories encompass a wide range of fields, including systems medicine and computational biology, providing a multifaceted perspective on understanding complex biological systems. This integration of diverse expertise enhances the center's position and reinforces its capabilities to address complex scientific challenges across various scales, from microscopic to macroscopic phenomena.
The primary objective of the PCNM is to establish a collaborative environment where wet-lab (experimental) and dry-lab (computational) research activities progress hand in hand. The integration of expertise and resources at the PCNM drives forward the frontiers of knowledge in network medicine at the cross-road of complex systems science, computational biology, preclinical and clinical research. By promoting synergy between different research approaches, the center aims to accelerate scientific discoveries and translate them into practical applications.
In recognition of its outstanding contributions and cutting-edge research, the PCNM organizes a flagship workshop serving as a platform for scholars from diverse fields to convene and exchange ideas. The workshop showcases the latest advancements in network medicine, from a broad perspective. Through keynote lectures, talks and poster presentations, participants engage in fruitful discussions, fostering collaborations, and inspiring new research directions. The workshop acts as a catalyst for interdisciplinary collaboration, pushing the boundaries of knowledge and promoting the translation of research findings into practical solutions that can benefit society as a whole.

Aim of the PCNM Workshop. The goal of this workshop is to serve as a significant gathering for leading scientists, providing an opportunity to share groundbreaking research, foster collaborations, and shape the future of network medicine and its applications in improving human health and well-being. The research of interest encompasses a broad spectrum of topics, including (but not limited to) the identification of pathogenetic processes, biomarker discovery for diagnosis, patient clustering for tailored therapies, and the study of population dynamics during epidemics and pandemics.
In this meeting, special emphasis will be given to the following topics:

- Multi-OMICS approaches to Network Medicine
- Clinical applications of Network Medicine
- Modeling and Explainable Analytical Methods for Network Medicine

KEYNOTE SPEAKER

Joseph Loscalzo
Brigham and Women’s Hospital & Harvard Medical School

INVITED SPEAKERS

Silvio Bicciato
University of Modena and Reggio Emilia

Leonard Prins
University of Padua

Vera Pancaldi
Tolouse Cancer Research Center

Fabio Vandin
University of Padua

REGISTRATION

To attend the workshop, registration is mandatory.

Registrations are welcome and are independent from the acceptance of oral contributions. Registration is free for PCNM members (63 members) and one of their collaborators (up to 63 seats).

For scholars external to the PCNM, we will consider free registrations up to the first 130 registered attendants: above this threshold, a small fee will apply (50 euros).

Note that we are currently working hard on the location to host all of us. In the case space limitations will be unavoidable (80 seats guaranteed), we will prioritize earlier registrations.

Registration link

CONTRIBUTIONS

Contributions are welcome as abstracts about published or unpublished research (one page abstract). We invite you to apply for one of the following formats:

Lab Flash talks: for a general description of the activities of the laboratories affiliated to the PCNM
Lab Poster for a general description of the activities of the laboratories affiliated to the PCNM
Poster for young researchers willing to present the results of a specific research activity (abstracts submitted by young researchers are welcome)

Contributions should be aligned with at least one of the following topics:

Multi-OMICS approaches to Network Medicine
Clinical applications of Network Medicine
Modeling and Explainable Analytical Methods for Network Medicine

Click on the button below to submit.

Submission link

IMPORTANT DATES

	July 07, 2023	Deadline for Registration (mandatory, even in absence of a contribution)
	July 25, 2023	Deadline for Contributions
	August 08, 2023	Notification of acceptance
	September 28, 2023	Workshop

PROGRAM

VENUE: Fondazione Ricerca Biomedica Avanzata VIMM, Via Giuseppe Orus, 2, 35129 Padova PD

Morning Session

Chair: Manlio De Domenico

Time		Speaker

09:00 Invited		Fabio Zwirner, Vice Rector for Research Manlio De Domenico (Department of Physics and Astronomy) Welcome, motivation and acknowledgements
9:15 Invited		Flavio Seno (Department of Physics and Astronomy) Roberto Vettor (Department of Medicine) Introduction to the Padua Center for Network Medicine
9:45 Invited		Rosario Rizzuto, Department of Biomedical Sciences Synergies with the National Center for gene therapy and drugs based on RNA technology
10:00 Keynote		Joseph Loscalzo, Brigham and Women’s Hospital & Harvard Medical School Defining Disease and Precision Therapeutics in the Era of Big Data Historically, scientific reductionism has provided the basis for our understanding of the causes of and treatments for disease. While this approach has often been successful, the great majority of diseases are complex and reflect many molecular interactions and responses defined by genomic context and environmental exposures. Given this complexity, the field of network medicine was developed, the fundamental principle of which is that a true understanding of disease definition, etiology, prognosis, and therapy requires a holistic approach to these complex molecular systems. As a basis for this approach, we build and utilize comprehensive, unbiased, (macro)molecular interaction networks. These networks are analyzed statically and dynamically, and variations within them can be used to characterize functional consequences for disease susceptibility or expression. Using the comprehensive network of all ascertainable protein-protein interactions, or interactome, we first demonstrated that the great majority of diseases are characterized by discrete subnetworks, or disease modules, within the interactome. In recent work, we showed that genetic variants associated with disease, both germline and somatic, are significantly enriched in sequences encoding protein-protein interaction interfaces compared to variants not associated with disease. These observations provided support for our work on exploring the network basis for different manifestations of the same disease (individualized disease phenotypes) within a cohort of patients with that disease. We developed the concept of individualized interactomes, or unique ‘reticulotypes,’ that reflect differential gene (and protein) expression for a given disease. Patient-specific reticulotypes may serve as the basis for characterizing the pathobiology of a disease phenotype in an individual patient. Furthermore, using a combination of network science-based analysis coupled with bioinformatic strategies, including deep learning approaches, we have utilized the interactome and the disease modules contained within it as a template for identifying unique drug targets. Thus, this approach effectively identifies specific pathway or protein targets for drug development, for constructing unique biomarkers for disease prognosis, and for repurposing approved drugs whose targets. In these ways, network medicine offers a novel path toward (re)defining and treating human disease in the modern era, and facilitates the development of precision medicine.
11:15		Coffee break
11:30		Fabio Vandin, Department of Information Engineering Patterns in cancer genomes through the lens of networks Sequencing technologies now allow measuring different features (e.g., somatic alterations) of a cancer genome at an outstanding level of detail for an unprecedented number of tumors. The resulting datasets provide an exceptional opportunity to gain insight into cancer development and progression by identifying patterns of mutations across different tumors. However, the identification of reliable patterns poses severe computational and statistical challenges, due to complex interactions among such features and the high dimensionality of the problem. In this talk I will discuss some recent works on network-based approachess to identify reliable and significant patterns from measurements of a large collection of tumors, including patterns associated with clinical or functional measures, and highlight some of the current and future challenges.
12:00		Flash Talks I Modeling and Explainable Analytical Methods for Network Medicine Giorgia Baron, Valeria D'Andrea, Marika Sartore, Francesco Marchetti, Michele Allegra, Francesco Zambelli, Giulia Cesaro, Giacomo Baruzzo

12:45

Lunch break

Afternoon Session

Chairs: Chiara Castellani and Chiara Romualdi

14:30 Invited		Silvio Bicciato, University of Modena and Reggio Emilia Computational analysis of single cell spatial omics data: challenges and opportunities The spatial organization of cells within tissues is crucial to understand homeostasis and disease, as biological function is intimately linked to the architecture of multicellular communities. Single-cell analyses, as RNA sequencing and other genomic modalities, have been transformative in expanding our ability to define cell identity and state through the interrogation of genomic, transcriptomic, or proteomic profiles in dissociated cells. However, these approaches fail to provide the complete characterization of cellular ecosystems, as information on the spatial relationships of cells within the tissue is lost. Emerging technologies for spatially resolved single cell genomics offer high-throughput solutions to measure the molecular characteristics of cells in situ. Single cell spatial profiling combines highly multiplexed imaging modalities, next generation sequencing or mass spectrometry to assess the spatial distribution of gene and protein expression within the native spatial context of cells. The rapid growth in these techniques and the massive amounts of data they produce dictate the development of novel computational methods to take advantage of this spatial information to derive biological insights. Here, we provide the current state, challenges, and future perspectives for the analysis of data from single cell spatially resolved technologies with a focus on methods for signal processing, identification of cell types and cellular neighborhoods, extraction of spatial metrics, inference of cell-cell interactions, and reconstruction of tissue architectures.
15:00 Invited		Vera Pancaldi, Tolouse Cancer Research Center Structure-function relationships in chromatin networks The availability of unprecedented datasets detailing the organization of chromatin across species, developmental stages, cell types and diseases invites an integrated analysis of genome organization in 3D and its biological significance. Recently developed methods to represent chromatin structure as a network of contacts between genomic regions facilitate the comparison between nuclear organization across conditions, adding a 4th dimension. Here we attempt to formalize a hypothesis according to which the topological properties of the chromatin network can be shaped by the context of the cell, impacting its phenotype. We used network theory approaches to study the organisation of several cellular processes, including transcription, replication and, more recently, the evolution of the genome, differentiation and oncogenesis.
15:30 Invited		Leonard Prins, Department of Chemical Sciences Systems Chemistry: A bottom-up approach towards complex chemical networks Complex networks play an important role in nearly all areas of science, ranging from sociology, to biology and physics, apart from chemistry. Chemistry has emerged as a science focused on the isolation, purification and characterization of molecules in order to establish structure-property relationships. This knowledge, together with the skill to synthesize virtually all desirable molecules, has allowed chemists to produce medicine, detergents, cosmetics, food additives, and so forth, for the benefit of society. Yet, the reductionistic approach strongly contrasts with the way chemistry is carried out by nature. Properties such as motion, adaptability, evolution, communication emerge from complex networks of molecules and cannot be ascribed to a single molecule. Consequently, the traditional chemical approach is not suitable for rationally designing synthetic systems that display life-like properties. Here, I will introduce Systems Chemistry, which is a new branch of chemistry aimed at understanding how properties emerge from chemical networks. I will discuss the progress in designing and understanding synthetic chemical networks. Examples from research groups at the Department of Chemical Sciences will then be used to show how complex chemical systems may contribute to network medicine.
16:00		Flash Talks II Clinical applications of Network Medicine Diego Perazzolo, Daniele Coraci, Vittoria Raimondi, Loredana Urso, Marta Vadori
16:30		Flash Talks III Modeling and Explainable Analytical Methods for Network Medicine Dario Righelli, Arianna Delicati, Beatrice Marcante, Manuela Orlandi, Veronica Tauro, Giacomo Bernava, Cristina Vincenzetto
17:00		Manlio De Domenico, Department of Physics and Astronomy The 1st year of the PCNM and Outlooks
17:15		Aperi-Poster Poster presentation by labs affiliated to the PCNM Poster presentation by young researchers
18:30		Closing