BEGIN:VCALENDAR VERSION:2.0 PRODID:-//CERN//INDICO//EN BEGIN:VEVENT SUMMARY:Modelling ecosystems in complex diseases DTSTART;VALUE=DATE-TIME:20250611T090000Z DTEND;VALUE=DATE-TIME:20250611T093000Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1654@cern.ch DESCRIPTION:Speakers: Francesca Buffa (Bocconi University )\nhttps://indic o.unina.it/event/91/contributions/1654/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1654/ END:VEVENT BEGIN:VEVENT SUMMARY:Inference of lineage hierarchies and growth mechanisms in cell pop ulations without tracking DTSTART;VALUE=DATE-TIME:20250611T103000Z DTEND;VALUE=DATE-TIME:20250611T103500Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1647@cern.ch DESCRIPTION:Speakers: Andrea Piras (University of Turin)\nhttps://indico.u nina.it/event/91/contributions/1647/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1647/ END:VEVENT BEGIN:VEVENT SUMMARY:Integrating experimental feedback improves generative models for b iological sequences DTSTART;VALUE=DATE-TIME:20250611T102500Z DTEND;VALUE=DATE-TIME:20250611T103000Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1646@cern.ch DESCRIPTION:Speakers: Giovanni Peinetti (Sorbonne Université/Politecnico di Torino)\nhttps://indico.unina.it/event/91/contributions/1646/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1646/ END:VEVENT BEGIN:VEVENT SUMMARY:Emergent time scales of epistasis in protein evolution DTSTART;VALUE=DATE-TIME:20250611T100000Z DTEND;VALUE=DATE-TIME:20250611T100500Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1644@cern.ch DESCRIPTION:Speakers: Leonardo Di Bari (Politecnico di Torino & Sorbonne U niversitè)\nhttps://indico.unina.it/event/91/contributions/1644/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1644/ END:VEVENT BEGIN:VEVENT SUMMARY:Fluctuations and the limit of predictability in protein evolution DTSTART;VALUE=DATE-TIME:20250611T100500Z DTEND;VALUE=DATE-TIME:20250611T102500Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1628@cern.ch DESCRIPTION:Speakers: Saverio Rossi (Sapienza università di Roma)\nhttps: //indico.unina.it/event/91/contributions/1628/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1628/ END:VEVENT BEGIN:VEVENT SUMMARY:Generative modelling for protein evolution and design DTSTART;VALUE=DATE-TIME:20250611T093000Z DTEND;VALUE=DATE-TIME:20250611T100000Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1538@cern.ch DESCRIPTION:Speakers: Francesco Zamponi (Sapienza Università di Roma)\nPr otein fitness landscapes frequently exhibit epistasis\, where the effect o f a mutation depends on the genetic context\, i.e.\, the rest of the prote in sequence. Epistasis increases landscape complexity\, often resulting in multiple fitness peaks. In its simplest form\, known as global epistasis\ , fitness is modeled as a non-linear function of an underlying additive tr ait. In contrast\, more complex epistasis arises from a network of (pairwi se or many-body) interactions between residues\, which cannot be removed b y a single non-linear transformation. Recent studies have explored how glo bal and network epistasis contribute to the emergence of functional bottle necks - fitness landscape topologies where two broad high-fitness basins\, representing distinct phenotypes\, are separated by a bottleneck that can only be crossed via one or a few mutational paths. I will introduce and a nalyze a simple model of global epistasis with an additive underlying trai t\, and demonstrate that functional bottlenecks arise with high probabilit y if the model is properly calibrated. These results underscore the necess ity of sufficient heterogeneity in mutational effects for the emergence of functional bottlenecks. Moreover\, the model agrees with experimental fin dings\, at least in small enough combinatorial mutational spaces.\n\nhttps ://indico.unina.it/event/91/contributions/1538/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1538/ END:VEVENT BEGIN:VEVENT SUMMARY:The Laplacian Renormalization Groups (LRG) unveils the structural organization of heterogeneous networks DTSTART;VALUE=DATE-TIME:20250611T080000Z DTEND;VALUE=DATE-TIME:20250611T083000Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1537@cern.ch DESCRIPTION:Speakers: Andrea Gabrielli (Department of Civil\, Computer Sci ence and Aeronautical Technologies Engineering\, University “Roma Tre” )\nHeterogeneous and complex networks represent the intertwined interactio ns between real-world elements or agents. Determining the multi-scale meso scopic organization of clusters and inter- twined structures is still a fu ndamental and open problem of complex network theory. By taking advantage of the recent Laplacian Renormalization Group [1-4] approach \, we scrutin ize informa- tion diffusion pathways throughout networks to shed further l ight on this issue. Based on inter- node communicability\, our definition provides a clear-cut framework for resolving the multi-scale mesh of struc tures in complex networks\, disentangling their intrinsic arboreal archite cture. As it does not consider any topological null-model assumption\, the LRG naturally permits the intro- duction of scale-dependent optimal parti tions and determines the existence of a particular class of nodes\, called “metastable” nodes\, that switching regions to which they belong at d ifferent scales\, are expected to play a central role in the communication between them and\, therefore\, in managing macroscopic effects of the who le network [5]. \n\n[1] P Villegas\, T Gili\, G Caldarelli\, A Gabrielli\, Laplacian renormalization group for heterogeneous networks\, Nature Physi cs 19 (3)\, 445-450 (2023) [2] P Villegas\, A Gabrielli\, F Santucci\, G C aldarelli\, T Gili\, Laplacian paths in complex networks: Information core emerges from entropic transitions\, Physical Review Research 4\, 033196 ( 2022) [3] A. Gabrielli\, D. Garlaschelli\, S. Patil\, M. A. Serrano\, Netw ork Renormalization\, https://arxiv.org/abs/2412.12988\, to appear on Natu re Review Physics (2025). [4] A. Poggialini\, P. Villegas\, M.A. Munoz\, A . Gabrielli\, Networks with Many Structural Scales: A Renormalization Grou p Perspective\, Phys. Rev. Lett. 134\, 057401 (2025) [5] P. Villegas\, A. Gabrielli\, A. Poggialini\, T. Gili\, Multi-scale Laplacian community dete ction in heterogeneous networks\, Phys. Rev. Res. 7\, 013065 (2025)\n\nhtt ps://indico.unina.it/event/91/contributions/1537/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1537/ END:VEVENT BEGIN:VEVENT SUMMARY:Exploring cooperative effects among features in explainable artifi cial intelligence DTSTART;VALUE=DATE-TIME:20250611T073000Z DTEND;VALUE=DATE-TIME:20250611T080000Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1536@cern.ch DESCRIPTION:Speakers: Sebastiano Stramaglia (UNIBA & INFN\, Sezione di Bar i)\nLeveraging the large body of work devoted in recent years to describe redundancy and synergy in higher order interactions among random variables \, we propose an adaptive version of a well- known metric of feature impor tance\, named Leave One Covariate Out (LOCO)\, to disentangle high- order effects involving a given input feature in regression problems. Applicatio ns to biological data sets will be described.\n\nhttps://indico.unina.it/e vent/91/contributions/1536/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1536/ END:VEVENT BEGIN:VEVENT SUMMARY:The role of criticality in the structure-function relationship in the human brain DTSTART;VALUE=DATE-TIME:20250611T070000Z DTEND;VALUE=DATE-TIME:20250611T073000Z DTSTAMP;VALUE=DATE-TIME:20260521T043928Z UID:indico-contribution-320-1535@cern.ch DESCRIPTION:Speakers: Silvia Scarpetta (Dept. of Physics "E.R.Caianiello" University of Salerno Laboratorio di Reti Neurali "Maria Marinaro)\nHealth y brains exhibit a rich dynamic repertoire with flexible and diverse spati otemporal pattern replays across microscopic and macroscopic scales.We hyp othesize that the system must operate near a critical regime for the funct ional repertoire to be fully explored\, and flexible dynamics to emerge.To test this hypothesis\, we employ a modular Spiking Neuronal Network model \, where each group of Leaky Integrate-and-Fire neurons represents a corti cal region.A learning rule based on Spike-Timing-Dependent Plasticity (STD P) is used to encode patterns of activations that prop- agate between modu les.The patterns exploit empirical information on the number of white-matt er fibers between regions. The model [1] displays two distinct dynamical r egimes: an uncorrelated low-rate state and a strongly correlated state\, m arked by a high Order Parameter value (indicating the similarity of sponta neous activity with one of stored patterns).These regimes are separated by either a first-order or second-order phase transition\, depending on the strength of global inhi- bition and structured connections. When the hyste resis loop shrinks\, a continuous phase transi- tion occurs\, and it opens up an extended region with high order parameter fluctuations (close a Wid om line with maxima of fluctuations).The model predictions are compared wi th empirical data from magnetoencephalographic (MEG) recordings in healthy adults. We show that the structural- function correlation is maximized wh en the model is the extended critical regime.Then\, the Lev- enshtein dist ance is used to quantify the similarity between the sequences of region ac tivations in neural avalanches from both the empirical data and the model simulations.Notably a similar reper- toire of sequence is observed in synt hetic data and MEG\, only when the model operates within the critical exte nded regime. \n\n[1]The role of criticality in the structure-function rela tionship in the human brain. M.Angiolelli S.Scarpetta et al. Physical Revi ew Research 2025\n\nhttps://indico.unina.it/event/91/contributions/1535/ LOCATION:Hotel Palazzo Alabardieri Sala Caracciolo URL:https://indico.unina.it/event/91/contributions/1535/ END:VEVENT END:VCALENDAR