BEGIN:VCALENDAR VERSION:2.0 PRODID:-//CERN//INDICO//EN BEGIN:VEVENT SUMMARY:Stories of Statistical Physics and Computational Biology DTSTART;VALUE=DATE-TIME:20241218T101000Z DTEND;VALUE=DATE-TIME:20241218T103000Z DTSTAMP;VALUE=DATE-TIME:20261017T053145Z UID:indico-contribution-260-1395@cern.ch DESCRIPTION:Speakers: Andrea Maria Chiariello (Dipartimento di Fisica Etto re Pancini\, Università di Napoli Federico II)\nWithin the cell nucleus o f eukaryotic organisms\, chromosomes are organized in a complex\, non-rand om three-dimensional (3D) spatial structure\, which is intimately linked t o vital functional purposes. Indeed\, a correct folding allows an efficien t communication between genes and their distal regulatory elements while\, if altered\, can cause severe diseases. Here I will discuss how Polymer P hysics\, combined with Molecular Dynamics simulations and Machine Learning based inference\, represent a powerful tool to quantitatively investigate the complexity of 3D organization of real genomes\, as highlighted by rec ent microscopy and biochemical experiments. I will show that simple physic al processes\, widely studied in Statistical Mechanics\, such as phase-sep aration of molecular aggregates and symmetry breaking mechanisms\, allow u s to make sense of recent experimental observations including the in olfac tory receptor choice in olfactory sensory neurons (OSN). Finally\, polymer models can be used to study the impact of disease-linked genetic mutation s or the effect of viral infections as SARS-CoV-2\, opening the way to new potential tools in Biomedicine.\n\nhttps://indico.unina.it/event/86/contr ibutions/1395/ LOCATION:Dipartimento di Fisica "Ettore Pancini" Aula Caianiello URL:https://indico.unina.it/event/86/contributions/1395/ END:VEVENT BEGIN:VEVENT SUMMARY:Epidemic Dynamics in Interconnected Populations: Scaling and Polic y Implications DTSTART;VALUE=DATE-TIME:20241218T093000Z DTEND;VALUE=DATE-TIME:20241218T095000Z DTSTAMP;VALUE=DATE-TIME:20261017T053145Z UID:indico-contribution-260-1393@cern.ch DESCRIPTION:Speakers: Antonio Scala (CNR)\nUnderstanding the dynamics of i nfectious disease spread in interconnected populations is crucial for effe ctive public health planning. In our increasingly mobile world\, tradition al modeling approaches often fall short in capturing the complexities of d isease transmission across vast distances. This paper presents an innovati ve framework that combines the conceptual simplicity of ordinary different ial equations (ODEs) with the predictive capabilities of computational mod els to analyze epidemic dynamics on interconnected networks. We derive sca ling laws for epidemic propagation delays using perturbation expansion tec hniques\, highlighting the influence of network topology and migration flu x. Our findings reveal the diminishing returns of mobility reduction polic ies in mitigating epidemic spread\, particularly after the outbreak has se ttled. This work contributes to a deeper understanding of the mechanisms d riving infectious disease dynamics\, providing quantitative insights for p ublic health authorities to assess risks and optimize response strategies. \n\nhttps://indico.unina.it/event/86/contributions/1393/ LOCATION:Dipartimento di Fisica "Ettore Pancini" Aula Caianiello URL:https://indico.unina.it/event/86/contributions/1393/ END:VEVENT BEGIN:VEVENT SUMMARY:Modeling the human genome through polymer physics DTSTART;VALUE=DATE-TIME:20241218T091000Z DTEND;VALUE=DATE-TIME:20241218T093000Z DTSTAMP;VALUE=DATE-TIME:20261017T053145Z UID:indico-contribution-260-1394@cern.ch DESCRIPTION:Speakers: Mattia Conte (Università di Napoli Federico II & IN FN)\nIn the nucleus of cells\, chromosomes have been discovered to self-or ganize into a complex spatial architecture that serves vital functional pu rposes as\, for instance\, genes have to establish specific physical conta cts with their distal DNA regulators to control transcriptional activities . However\, how the system self-assembles to shape the folding of our geno me and its functions is only poorly understood. In this talk\, I discuss p rincipled models of interacting polymers from statistical mechanics to inv estigate the mechanisms whereby distal DNA sequences recognise and interac t with each other. Those theories are validated against independent experi ments\, opening to new tools for real-world applications\, such as the pre diction of the effects of disease-associated mutations\, linked to congeni tal disorders or cancer\, on genome 3D structure.\n\nhttps://indico.unina. it/event/86/contributions/1394/ LOCATION:Dipartimento di Fisica "Ettore Pancini" Aula Caianiello URL:https://indico.unina.it/event/86/contributions/1394/ END:VEVENT BEGIN:VEVENT SUMMARY:Predictive polymer models of genome 3D structure DTSTART;VALUE=DATE-TIME:20241218T095000Z DTEND;VALUE=DATE-TIME:20241218T101000Z DTSTAMP;VALUE=DATE-TIME:20261017T053145Z UID:indico-contribution-260-1396@cern.ch DESCRIPTION:Speakers: Simona Bianco ()\nChromosomes have a complex spatia l structure that serves vital functional purposes\, yet their self-organiz ation principles are largely unknown. I discuss our recent work combining polymer physics and machine learning to understand how chromosomes are fol ded and regulated in the cell nucleus. After a brief overview of recent ex perimental advances to measure chromosome 3D structure\, I discuss our phy sics models showing that phase transition mechanisms can control chromosom e architecture and its link with gene regulation and cell function. Severa l experiments have confirmed those models\, notably their predictions on h ow genetic mutations result in diseases such as congenital disorders\, ope ning the way to novel applications in biomedicine.\n\nhttps://indico.unina .it/event/86/contributions/1396/ LOCATION:Dipartimento di Fisica "Ettore Pancini" Aula Caianiello URL:https://indico.unina.it/event/86/contributions/1396/ END:VEVENT END:VCALENDAR