Biological Physics and Statistical Mechanics

Contribution List

136. Theory and experiments on protein chaperone function

Paolo De Los Rios (EPFL, Lausanne)

6/8/26, 2:30 PM

58. Shared dynamics, different embedding geometries: multi-regional study of decision-making and spatial-memory task

Eleonora Russo (Scuola Superiore Sant'Anna, Pisa)

6/8/26, 3:00 PM

Invited talk

59. Dynamics of sparse excitatory-inhibitory networks

Alessandro Ingrosso (Radboud University, Nijmegen)

6/8/26, 3:30 PM

Invited talk

In this work, we build on a recently developed Dynamical Mean Field Theory method to investigate the dynamical behavior of heterogeneous rate and spiking networks defined on finite-connectivity graphs. We show how topological disorder is sufficient to induce chaos in networks composed of distinct excitatory and inhibitory populations, and study how different degree distributions impact the...

60. Predicting spatial memory performance from scaling of hippocampal activity

Fabrizio Lombardi (Università di Padova)

6/8/26, 4:30 PM

Invited talk

64. Symmetry breaking and avalanche shapes in modular networks

Antonio De Candia

6/8/26, 5:00 PM

Experimental evidence suggests that the healthy brain operates near a critical regime, characterized by scale-free neuronal avalanches.
Recent research has increasingly focused on the mean temporal profiles of neuronal avalanches, as a more stringent and reliable test for criticality. Scaling arguments predict that, when appropriately rescaled, the mean temporal profiles of avalanches of...

65. Temporal Organization of Neuronal Avalanches Constrained by Structural Connectivity in MEG

Gianmarco Cafaro

6/8/26, 5:15 PM

The study of neuronal activity through electrophysiological recordings provides a framework to investigate brain function and how biological alterations may influence disease onset. Different analytical approaches across multiple brain scales (single neurons, neural networks, neural mass, and whole-brain activity) yield distinct biomarkers, offering insight into where and how system-level...

66. Generative modeling of functional biosequences from artificial selection experiments

Stefano Crotti

6/8/26, 5:30 PM

SELEX experiments aim at identifying short RNA strands that specifically bind to a given target molecule, through several successive rounds of \textit{in vitro} selection. This talk presents ongoing work on a mathematical model learned on SELEX data with a twofold objective: gaining insight about the biophysical mechanisms underlying the selection process, and generating novel RNA sequences...

78. Biologically relevant finite-size effects in a driven lattice gas with particle pausing and dynamical defects

Lorenzo Vito Dal Zovo (Politecnico di Torino)

6/8/26, 5:40 PM

In this work we present a study of the totally asymmetric simple exclusion process
with pausing particles (pTASEP), a model initially introduced to describe RNAP dynamics during
transcription. We extend previous mean-field approaches and demonstrate that the pTASEP is
equivalent to the exclusion process with dynamical defects (ddTASEP), thus broadening the scope
of our investigation to a...

41. Physics meets biology in the lungs

Pietro Cicuta

6/9/26, 9:00 AM

Invited talk

40. Active phase separation

Cesare Nardini (SPEC/CEA - Université Paris-Saclay)

6/9/26, 9:30 AM

Invited talk

42. Chromatin Organization and Interaction Footprints: A Two-State Model for M-FISH Data Analysis Based on Polymer Physics

Andrea Parmeggiani (Université de Montpellier)

6/9/26, 10:00 AM

Invited talk

67. Ensemble Theory of Active Fluctuations

Roman Belousov

6/9/26, 10:30 AM

Living matter subsists on active, nonequilibrium processes. At small scales, physical theories of these processes compensate for a lack of statistical-mechanics foundations, available for equilibrium systems, with phenomenological laws. Using advances in first-principle microcanonical methods, we develop an ensemble theory of active fluctuations and illustrate its application to cell sorting.

71. Exchange controls surface condensates

Riccardo Rossetto

6/9/26, 10:45 AM

Biological membranes often exhibit heterogeneous protein patterns, which cells control. Some patterns, such as the polarity spot in budding yeast, can be conceptualized as surface condensates, formed by physical interactions between constituents. However, the behaviour resulting from the interplay of physical interactions and material exchange between surface and bulk remains unclear. To...

72. Enzyme-driven phase separation

Damiano Andreghetti

6/9/26, 11:30 AM

The growth of signaling domains on cell membranes is reminiscent of
coarsening in equilibrium phase separation, although the process is
intrinsically non-equilibrium and driven by energy-consuming enzymatic
cycles that switch signaling molecules between distinct states. We
develop a minimal model of this enzyme-driven phase ordering process.
Starting from microscopic reaction kinetics, we...

73. Directed Autonomous Motion and Chiral Separation of Self-Propelled Janus Particles in Convection Roll Arrays

Poulami Bag

6/9/26, 11:45 AM

Self-propelled Janus particles hold enormous promise for nanotechnology and biomedical applications, but their inherently random motion limits practical utility. In this study, we show through computer simulations that we can control the movement of chiral active Janus particles effectively, achieving over 60% efficiency by placing them in a line of rotating flows. Our approach does not...

74. Uncoupling density- and adhesion-driven rigidity transitions in embryonic tissues

Elisa Floris

6/9/26, 12:00 PM

Organism development occurs through sequences of astonishingly precise spatiotemporal changes, along which embryonic tissues switch between fluid- and solid-like states, arising from non-linear interactions among cellular constituents. In this context, tissue fluidization observed in vivo in zebrafish embryos was interpreted, within the framework of rigidity percolation, as a rigid-to-floppy...

68. Non-Equilibrium Thermodynamics of pulsating active matter

Michele Antonioli

6/9/26, 12:15 PM

Flash talk

The cardiac tissue shows deformation patterns made of spiral defects as a precursor of
cardiac arrest [1]. Such patterns are captured by pulsating active matter (PAM), which
considers particles that independently change their size by an active pulsation mechanism
that drives the system out-of-equilibrium; the competition between steric repulsion and local
synchronization allows for a...

69. MesoMem: A mesoscale membrane model based on an additive potential

Pietro Sillano

6/9/26, 12:30 PM

Flash talk

Bridging the gap between atomistic detail and continuum mechanics remains a central challenge in modeling mesoscopic biological membranes. This regime governs key processes such as membrane reshaping and protein-induced deformation, where the interplay between molecular features and mechanical response is crucial.

In this talk, I introduce MesoMem: a solvent-free, one-particle-thick,...

70. Persistence-driven enhancement of enzyme diffusion

Giuliano Migliorini

6/9/26, 12:40 PM

Flash talk

In the past fifteen years, several experiments have reported an increase in the diffusion of catalytically active enzymes compared to their passive state in the absence of substrate. While these observations remain debated and appear to depend on the measurement technique, they have stimulated significant theoretical interest due to their potential biological and physical implications.

Most...

117. Boosted continuous Wang-Landau Algorithm: A Novel Approach for the Sampling of Soft Matter

Camilla Spreti (Istituto Nazionale di Fisica Nucleare - Università di Trento)

6/9/26, 12:50 PM

The Wang–Landau algorithm is a powerful Monte Carlo method designed to reconstruct the density of states of a system in a self-consistent manner, by uniformly exploring its energy spectrum. This approach enables the efficient sampling of rare configurations and is particularly well-suited for systems characterised by rugged energy landscapes. In this work, we illustrate a continuous variant of...

44. Configurational entropy and efficient sampling of randomly double-folding chromosome-like polymers

Angelo Rosa (SISSA, Trieste)

6/9/26, 2:30 PM

45. Polymer physics of ecDNA 3D structure and function

Mattia Conte (Università di Napoli "Federico II")

6/9/26, 3:00 PM

75. All-Atom Simulation of Co-Translational Protein Folding Reveals Functional, Pathogenic, and Pharmacological Roles of Folding Intermediates

Pietro Faccioli

6/9/26, 3:30 PM

In this talk, we shall review how recent advances in physics-based enhanced simulation methods for rare molecular transitions now enable accurate prediction of co-translational protein folding pathways at atomic resolution. These approaches have revealed unexpected functional, pathological, and pharmacological roles for metastable states that are transiently populated during folding.

In...

135. Self-assembly Monte Carlo reveals localized entanglement in giant polymer melts

Enrico Fornasa (SISSA)

6/9/26, 3:45 PM

76. Entangled motifs generate energetic frustration in good-folding sequences within lattice protein models

Antonio Trovato (University of Padova and INFN - Padova Section)

6/9/26, 4:30 PM

Entangled lasso motifs are looped chain portions intertwined with another chain fragment. Non-covalent lassos are present in one third of protein domains, with energetic frustration detected between their end residues [1]. The presence of misfolded protein sub-populations is connected to their entanglement properties [2]. Such misfolded species are kinetic traps, native-like in several...

77. How one gene wins: a two-step symmetry-breaking model of olfactory receptor choice

Martin Miranda (Helmholtz Zentrum München)

6/9/26, 4:45 PM

In the mammalian olfactory epithelium, each mature sensory neuron expresses a single olfactory receptor (OR) gene out of more than a thousand candidates, through a still-unknown mechanism (Monahan & Lomvardas 2015). We propose a two-step selection process: the nucleus first assembles several inter-chromosomal hubs that bring OR-specific enhancers into contact with dozens of OR genes (Monahan...

17. Biological Knowledge or just Sparsity? Uncovering the True Driver in Pathway-Informed Neural Networks

Isabella Caranzano (Università di Torino, Dipartimento di Scienze Mediche), Prof. Tiziana Sanavia (Università di Torino, Dipartimento di Scienze Mediche)

6/9/26, 5:00 PM

Objective:
Pathway-informed neural networks have become popular in biomedical research for incorporating biological knowledge into deep learning models, especially when dealing with high-dimensional omics data. These architectures are assumed to benefit from biological priors (e.g., gene-pathway associations), which are expected to enhance predictive performance and interpretability. However,...

30. Steering Sequence Generation in Protein Language Models through Iterative Lookback Monte Carlo Sampling

Francesco Calvanese (IPhT-Paris Saclay, Sorbonne University)

6/9/26, 5:15 PM

Protein language models (pLMs) enable the generation of novel protein sequences by leveraging large-scale evolutionary information, but steering generation toward desired physicochemical properties remains challenging. Existing approaches often either reduce sequence diversity or require costly retraining. We introduce Iterative Lookback Monte Carlo (ILMC), a training-free inference-time...

33. Denoising heterogeneous proximity networks for spatial reconstruction in DNA microscopy

Federico Scarpati (Sorbonne Université)

6/9/26, 5:30 PM

DNA microscopy is a novel imaging-by-sequencing technique that encodes spatial information into a proximity network of sequenced molecular barcodes, producing a geometric graph representing the probed sample rather than a conventional image. Inferring spatial coordinates from the topology of such graphs is a non-trivial inverse problem, made harder by experimental artifacts that alter the...

122. A simple dynamical system for modelling a tip link

Simone Sciandra (Politecnico di Torino)

6/9/26, 5:40 PM

This talk aims to develop a simple dynamical model of the tip link, a protein that connects the stereocilia in the hair cells of the cochlea. In particular, the model’s goal is to reproduce the force-extension behavior observed in force ramp experiments done with optical tweezers on one of the two proteins that compose the tip link, Protocadherin 15, and to capture domain unfolding.

The...

46. Inference of ecological constraints in microbial communities

Simona Cocco (CNRS, Paris)

6/10/26, 9:00 AM

Invited talk

47. Navigating RNA Sequence Space: Generative Models, Biophysics, and High-Throughput Experiments

Martin Weigt (Sorbonne Université)

6/10/26, 9:30 AM

Invited talk

48. Integrated Computational Framework for Protein–Protein Interaction Characterization: From Binding Site Identification to Docking Evaluation

Edoardo Milanetti (Link Campus University, Roma)

6/10/26, 10:00 AM

Invited talk

Protein–protein interactions are fundamental to cellular function and represent key targets for therapeutic design, including antibodies and antibody mimetics. However, accurate prediction of binding interfaces and docking conformations remains a major challenge in computational structural biology.

A computational framework for the characterization of biomolecular recognition is presented,...

61. Navigating the attractor landscape of single cells

Federico Bocci (Radboud University)

6/10/26, 10:30 AM

Modern single cell sequencing technologies enable us to probe cellular processes at unprecedented resolution, while introducing new theoretical challenges. A major difficulty lies in constructing dynamical models of cell behavior, as these technologies capture only a single snapshot of a cell's state, thereby preventing the observation of temporal dynamics. In this talk, I will discuss how we...

80. A statistical-physics approach for codon usage optimization

Pierpaolo Bruscolini (University of Zaragoza)

6/10/26, 10:45 AM

The degeneracy of the codon alphabet allows different codons to translate to the same amino acid, and different species show different patterns of codon usage. Using the wrong pattern reduces protein expression; however, using the most frequent codon for each amino acid does not necessarily maximize protein expression, which is the goal of codon "optimization".

Due to the complex (and...

62. Multi-Omics Topic Modeling for Cancer Subtype Classification

Filippo Valle (Istituto Nazionale di Fisica Nucleare)

6/10/26, 11:30 AM

The integration of transcriptional data with post-transcriptional regulatory layers, such as microRNA-mediated processes, is critical for identifying driver genes and characterizing subtypes in heterogeneous diseases like cancer. Here, we present a topic modeling approach based on a hierarchical stochastic block model, designed to integrate diverse multi-omics datasets. We applied this method...

63. Universal diversity scaling in component systems, from proteomes to large language models

Andrea Mazzolini (Istituto Nazionale di Fisica Nucleare)

6/10/26, 11:45 AM

The diversity of components and functions in complex systems is at the basis of the system's well-being and resilience, with prominent examples in ecology, genomics, or technological systems. A hallmark of the system's diversity is Heaps’ law, which is the sub-linear growth of the number of distinct components in a modular system, i.e., the diversity, with its size. Its emergence is widespread...

83. Modeling Protein Sequence Evolution as an Ornstein-Uhlenbeck Process in a Latent Space

Matteo De Leonardis (Politecnico di Torino)

6/10/26, 12:00 PM

High-throughput directed evolution produces longitudinal sequence libraries that are ideal for probing local fitness neighborhoods but often underpowered for global inference tasks such as contact prediction. We present an unsupervised generative model that integrates directed-evolution sequencing time series with natural homologs. We project sequences into a low-dimensional latent space...

84. Matrix-Product Belief Propagation for continuous-state-space variables

Federico Florio (Politecnico di Torino)

6/10/26, 12:15 PM

Computation of observables in discrete stochastic, possibly conditioned, dynamics over large sparse networks is at the basis of a myriad of applications. The Matrix-Product Belief Propagation method allows a semi-analytical estimation of such observables in tree-like networks with a controlled error that depends on the bond size, that is the dimension of the employed square matrices. Its...

81. What does the intrinsic dimension of single-cell transcriptomes actually measure?

Leonardo Agasso (Istituto Nazionale di Fisica Nucleare)

6/10/26, 12:30 PM

The intrinsic dimension (ID) of gene expression profiles has recently been proposed as a geometric potency score for scRNA-seq data. We test what fraction of this signal reflects genuine manifold geometry versus marginal statistics of gene expression, by preserving per-gene expression distributions while destroying co-expression structure. Across many differentiation lineages, the ID drop by...

82. Sparse generative models of protein sequences sample larger spaces at comparable experimental success rates

Roberto Netti (Sorbonne Université)

6/10/26, 12:40 PM

Flash talk

Boltzmann Machines trained on evolutionary sequence data have emerged as a powerful paradigm for the data-driven design of artificial proteins. However, the relationship between model architecture, specifically parameter density, and experimental performance remains poorly understood. Here, we investigate this relationship using the Chorismate Mutase enzyme family as a model system. We compare...

5. Model-based inference enables cross-species retrieval of DNA replication origins

Irene Pellini (Max Planck School Matter to Life)

6/10/26, 12:50 PM

Biochemical assays for replication origin identification are costly and time-consuming, motivating the development of computational approaches based on population sequencing data (DNA abundance profiles). However, accurate identification of DNA replication origins from such data remains challenging because origin firing is inherently stochastic: many origins fire inefficiently or are passively...

52. Microscale and mesoscale patterns of infectious disease transmission

Luca Ferretti (University of Oxford)

6/11/26, 9:00 AM

Invited talk

106. Causal variational approach for epidemic inference

Anna Paola Muntoni (Politecnico di Torino)

6/11/26, 9:30 AM

53. Brain wiring at different temperatures

Carlotta Martelli (Johannes Gutenberg-Universität Mainz)

6/11/26, 10:00 AM

85. Optimal sensing in confined environments

Laeschkir Würthner (EMBL Heidelberg)

6/11/26, 10:30 AM

Sensing and inferring concentrations in the environment is a relevant task for various life-like behaviors ranging from efficient navigation to cell-cell communication. Seminal work by Berg and Purcell focusing on bacterial chemotaxis demonstrated that the precision with which concentrations can be sensed by bacteria is fundamentally limited by molecular counting noise. Interestingly, as shown...

86. Polymer Physics Approach to ecDNA folding

Matteo Olimpo (Istituto Nazionale di Fisica Nucleare)

6/11/26, 10:45 AM

Flash talk

Extrachromosomal DNA (ecDNA) drives oncogene amplification through complex structural rearrangements that radically alter 3D chromatin topology. Here, we introduce a physical framework to predict the de novo 3D architecture of ecDNA in silico. By modeling DNA as a polymer driven to fold by interacting molecules (binders), we utilize the PRISMR machine-learning algorithm to infer the...

87. Predicting the 3D cancer genome architecture via polymer physics

Ciro Di Carluccio (Istituto Nazionale di Fisica Nucleare)

6/11/26, 11:30 AM

Flash talk

Recent literature increasingly highlights the crucial role of non-coding alterations in oncogenesis. In particular, structural variants (SVs) can drastically reorganize the three-dimensional architecture of the genome, leading to phenomena such as enhancer hijacking and the reorganization of chromatin domains. Theoretical models of chromosome folding are emerging as great tools to...

91. RNA Mamba: a selective state space model trained on all RNA families

Giovanni Peinetti (Politecnico di Torino/ Sorbonne Université)

6/11/26, 11:45 AM

We introduce RNA Mamba, a generative selective state space model trained jointly on thousands of RNA families from the RFAM dataset. Mamba state space models are an alternative to Transformers, offering linear scaling with sequence length and the ability to process long-range dependencies efficiently. We incorporate structural information into the model using a structural tokenization scheme...

92. Comparative polymer modelling of large-scale 3D genome re-arrangements upon different viral infections

Andrea Fontana (Università di Napoli "Federico II" and INFN Napoli)

6/11/26, 12:00 PM

Viruses can re-structure the architecture of host cells genome and also alter their epigenomic landscape. In this study, we investigate with polymer physics modelling virus induced genome re-organization by using available datasets from different viral infections causing: COVID-19 syndrome (SARS-CoV-2 virus), human common cold (HCoV-OC43 virus) and avian influenza (IAV-H5N1 virus) [1,2]. By...

89. In search of the Hot-Spots and of the Communication Network of the Cellular Prion Protein using Information-Theoretical Measures

Alessia Guadagnin Pattaro (Istituto Nazionale di Fisica Nucleare)

6/11/26, 12:15 PM

The cellular prion protein (PrP^C) is mostly expressed in the brain and in the central nervous system as a structure with a disordered region and a globular part, but it has no clear role in the organisms in which it is present. For reasons that are still unknown, PrP^C spontaneously converts to its misfolded counterpart PrP^Sc, which accumulates in tissues and...

7. Nonlinear dynamics of heart and brain

Irene Pellini (Max Planck School Matter to Life)

6/11/26, 12:30 PM

The core function of the heart and brain arises from the coordinated interaction of their cells.
Both organs rely on excitable units -- cardiomyocytes and neurons -- that propagate electrical signals when a specific threshold is exceeded.
Despite this similarity, the two organs exhibit opposed collective behavior due to marked differences in intercellular dynamics and network topology.
In...

90. Understanding Ridge Regression for Antibody-Antigen Binding Inference with Random Matrix Theory

Alessandro Corso (Università di Padova)

6/11/26, 12:40 PM

Predicting antibody-antigen binding affinity from sequence data is a central challenge in computational immunology and virology. Linear models trained on deep mutational scanning (DMS) experiments provide a tractable approximation, but their generalization performance depends strongly on data structure, dimensionality, and regularization. Here, we develop an analytical framework to...

88. Free-Energy Landscapes of DNA Kinking: Pathways Beyond Harmonic Elasticity

Arianna Fassino (KU Leuven)

6/11/26, 12:50 PM

Flash talk

DNA in vivo is frequently subjected to strong mechanical deformations during a variety of biological processes, including looping, supercoiling, and DNA–protein interactions. While coarse-grained models often describe DNA as a smoothly bendable polymer, both experimental and theoretical studies indicate that mechanical stress can induce localized kinks that significantly alter its mechanical...

49. Inheritance entropy: A model-independent method to probe the hereditary structure of cell lineage trees

Andrea Cavagna (CNR-ISC, Roma)

6/11/26, 2:30 PM

Invited talk

51. Patterns and Coexistence in Large Spatial Ecosystems

Sandro Azaele (Università di Padova)

6/11/26, 3:00 PM

54. Experimentally accessible measurement of irreversibility in stochastic systems by categorizing single-molecule displacements

Stefano Bo (King's College London)

6/11/26, 3:30 PM

93. Linking complex microbial interactions and dysbiosis through a disordered Lotka–Volterra model

Samir Suweis (Università di Padova)

6/11/26, 4:30 PM

The rapid advancement of environmental sequencing technologies, such as metagenomics, has significantly enhanced our ability to study microbial communities. The eubiotic composition of these communities is crucial for maintaining ecological functions and host health. Species diversity is only one facet of a healthy community’s organization; together with abundance distributions and interaction...

94. A Dynamical Metabolic Scaling Theory of Forest Communities

Davide Bernardi (Istituto Nazionale di Fisica Nucleare)

6/11/26, 4:45 PM

Although ecological communities exhibit pervasive scaling relations between size, abundance, and resource availability, the dynamical mechanisms underlying these patterns remain poorly understood. Using metabolic scaling arguments, we develop a dynamical framework for forest communities based on spatially-explicit seed dispersal, growth, local competition, and global resource constraints. By...

95. Will a time-varying complex system be stable?

Christian Grilletta (Università di Padova)

6/11/26, 5:00 PM

Ecological communities are theoretically predicted to be unstable upon crossing a critical threshold of species diversity, as first shown by May. Yet, natural ecosystems exhibit remarkable stability, suggesting the presence of additional stabilizing mechanisms. While the diversity-stability relation is typically assessed assuming fixed interactions, real ecosystems evolve in intrinsically...

96. Generalized Lotka-Volterra model on sparse asymmetric graphs: local equations and Random Matrix Theory

Pietro Valigi (University of Bath)

6/11/26, 5:15 PM

Real ecosystems, characterised by sparse and asymmetric interactions, represent highly complex disordered systems that pose a fundamental challenge for theoretical analysis. To address this, we analyse the generalised Lotka-Volterra model on sparse graphs, with and without demographic noise [1]. Drawing on the success of local closures in spin-glass dynamics [2] and combinatorial optimisation,...

111. Generalized Lotka-Volterra model with sparse interactions: non-gaussian distributions and topological multiple-equilibria phase

Tommaso Tonolo (Gran Sasso Science Institute)

6/11/26, 5:30 PM

In this talk we study the equilibrium phases of a generalized Lotka-Volterra model characterized by random, sparse, and symmetric
interactions. The equilibrium distribution of species abundances is obtained by means of the cavity method and the Belief Propagation
equations, which allow for an exact solution on sparse networks. Our results reveal a rich and nontrivial phenomenology that...

123. A stochastic framework for plankton biodiversity

Giorgio Vittorio Visco (Università di Padova)

6/11/26, 5:40 PM

Planktonic communities play a critical role in global biogeochemical cycles and marine ecosystems. However, their quantitative modelling is heavily constrained by the complexity of the seascape. Despite theoretical advances, recent models remain largely restricted to numerical simulations, leaving some open questions: What governs the evolution of plankton biomass? What is the interplay...

56. Resource allocation strategies behind rate-yield phenotypes in E.coli

Valentina Baldazzi (INRIA MACBES, Université Côte d'Azur)

6/12/26, 9:30 AM

57. Mechano-chemistry of C. Elegans elongation and how to infer forces in vivo

Silvia Grigolon (CNRS, Paris)

6/12/26, 10:00 AM

97. A Hopfield Model of Multidrug Adaptive Resistance

Martin Garic (Ecole Normale Supérieure)

6/12/26, 10:30 AM

101. Enhancing ribozyme thermostability via physical and generative modeling

Lorenzo Rosset

6/12/26, 10:45 AM

28. A statistical physics framework for mutation-rate in expanding and bottlenecked populations

Simone Pompei (IFOM ETS, The Airc Institute of Molecular Oncology)

6/12/26, 11:30 AM

The classical Luria–Delbrück theory links stochastic dynamics to parameter inference in expanding populations, but relies on assumptions typically violated in living cells and standard experimental designs.

By modeling stochastic population dynamics, we show that growing colony-size distributions and the empirical site frequency spectrum are distinct projections of the same...

102. Towards co-evolution-aware ancestral sequence reconstruction: beyond site-independent models

Alya Zeinaty (CQSB, Sorbonne Université & Chimera, Sapienza Università)

6/12/26, 11:45 AM

103. Optimal Maturation Protocols for High-Affinity Antibody Targets

Marian Huot (ENS Paris)

6/12/26, 12:00 PM

104. Temperature Increases The Target Size Of Compensatory Evolution

Moulikta Sanjeev

6/12/26, 12:15 PM

98. Leveraging Single-Cell Analysis and Trajectory Inference to Dissect Phenotypic Heterogeneity in Colorectal Cancer Organoids

Letizia Pizzini (Università degli Studi di Torino)

6/12/26, 12:30 PM

99. Overflow transition as a Nash equilibrium in populations of interacting cells

Daniele Carichini

6/12/26, 12:40 PM

100. AI-enhanced electrostatic calculation via NextGenPB

Enrico Ortu

6/12/26, 12:50 PM

120. A Dynamical Metabolic Scaling Theory of Forest Communities

Davide Bernardi (Department of Physics and Astronomy, University of Padova & INFN Padova, Italy)

Although ecological communities exhibit pervasive scaling relations between size, abundance, and resource availability, the dynamical mechanisms underlying these patterns remain poorly understood. Using metabolic scaling arguments, we develop a dynamical framework for forest communities based on spatially-explicit seed dispersal, growth, local competition, and global resource constraints. By...

126. A Hopfield Model of Multidrug Adaptive Resistance

Martin Garic (Ecole Normale Supérieure)

Understanding bacterial adaptation to multiple antibiotics is a central problem in evolutionary biology. While multiple studies have investigated how adaptation to one antibiotic affects resistance to others, what governs these interactions remains unclear. Here, we propose a generalized Hopfield model to describe the evolutionary dynamics of antibiotic resistance, where binary spins represent...

29. A statistical-physics approach for codon usage optimization

Dr Pierpaolo Bruscolini (Dep. de Física Teórica & BIFI, University of Zaragoza)

The degeneracy of the codon alphabet allows different codons to translate to the same amino acid, and different species show different patterns of codon usage. Using the wrong pattern reduces protein expression; however, using the most frequent codon for each amino acid does not necessarily maximize protein expression, which is the goal of codon "optimization".

Due to the complex (and...

50. A. Altieri

Ada Altieri (MSC Université Paris Cité)

114. All-Atom Simulation of Co-Translational Protein Folding Reveals Functional, Pathogenic, and Pharmacological Roles of Folding Intermediates

Pietro Faccioli (U. Milan-Bicocca and INFN)

In this talk, we shall review how recent advances in physics-based enhanced simulation methods for rare molecular transitions now enable accurate prediction of co-translational protein folding pathways at atomic resolution. These approaches have revealed unexpected functional, pathological, and pharmacological roles for metastable states that are transiently populated during folding.

In...

79. Biological Knowledge or just Sparsity? Uncovering the True Driver in Pathway-Informed Neural Networks

Isabella Caranzano

113. Biologically relevant finite-size effects in a driven lattice gas with particle pausing and dynamical defects

Lorenzo Vito Dal Zovo (Politecnico di Torino)

In this work we present a study of the totally asymmetric simple exclusion process
with pausing particles (pTASEP), a model initially introduced to describe RNAP dynamics during
transcription. We extend previous mean-field approaches and demonstrate that the pTASEP is
equivalent to the exclusion process with dynamical defects (ddTASEP), thus broadening the scope
of our investigation to a...

109. Comparative polymer modelling of large-scale 3D genome re-arrangements upon different viral infections

Andrea Fontana (Università di Napoli "Federico II" and INFN Napoli)

Viruses can re-structure the architecture of host cells genome and also alter their epigenomic landscape. In this study, we investigate with polymer physics modelling virus induced genome re-organization by using available datasets from different viral infections causing: COVID-19 syndrome (SARS-CoV-2 virus), human common cold (HCoV-OC43 virus) and avian influenza (IAV-H5N1 virus) [1,2]. By...

128. Denoising heterogeneous proximity networks for spatial reconstruction in DNA microscopy

Federico Scarpati

4. Directed Autonomous Motion and Chiral Separation of Self-Propelled Janus Particles in Convection Roll Arrays

Poulami Bag

Self-propelled Janus particles hold enormous promise for nanotechnology and biomedical applications, but their inherently random motion limits practical utility. In this study, we show through computer simulations that we can control the movement of chiral active Janus particles effectively, achieving over 60% efficiency by placing them in a line of rotating flows. Our approach does not...

21. Enhancing ribozyme thermostability via physical and generative modeling

Lorenzo Rosset

Enhancing enzyme thermostability is critical for applications ranging from industrial biocatalysis to mRNA vaccine storage and gene therapy. While significant progress has been made in stabilizing proteins, engineering thermostable RNA ribozymes remains a challenge. In this work, we present a computational strategy to stabilize Group I Intron ribozymes that are functional at room temperature...

10. Ensemble Theory of Active Fluctuations

Roman Belousov (European Molecular Biology Laboratory (EMBL))

Living matter subsists on active, nonequilibrium processes. At small scales, physical theories of these processes compensate for a lack of statistical-mechanics foundations, available for equilibrium systems, with phenomenological laws. Using advances in first-principle microcanonical methods, we develop an ensemble theory of active fluctuations and illustrate its application to cell sorting.

112. Entangled motifs generate energetic frustration in good-folding sequences within lattice protein models

Antonio Trovato (University of Padova and INFN - Padova Section)

Entangled lasso motifs are looped chain portions intertwined with another chain fragment. Non-covalent lassos are present in one third of protein domains, with energetic frustration detected between their end residues [1]. The presence of misfolded protein sub-populations is connected to their entanglement properties [2]. Such misfolded species are kinetic traps, native-like in several...

18. Enzyme-driven phase separation

Damiano Andreghetti (Politecnico di Torino, DISAT)

The growth of signaling domains on cell membranes is reminiscent of
coarsening in equilibrium phase separation, although the process is
intrinsically non-equilibrium and driven by energy-consuming enzymatic
cycles that switch signaling molecules between distinct states. We
develop a minimal model of this enzyme-driven phase ordering process.
Starting from microscopic reaction kinetics, we...

8. Exchange controls surface condensates

Riccardo Rossetto (Max Planck Institute for Dynamics and Self-Organization)

Biological membranes often exhibit heterogeneous protein patterns, which cells control. Some patterns, such as the polarity spot in budding yeast, can be conceptualized as surface condensates, formed by physical interactions between constituents. However, the behaviour resulting from the interplay of physical interactions and material exchange between surface and bulk remains unclear. To...

22. Free-Energy Landscapes of DNA Kinking: Pathways Beyond Harmonic Elasticity

Arianna Fassino (KU Leuven)

DNA in vivo is frequently subjected to strong mechanical deformations during a variety of biological processes, including looping, supercoiling, and DNA–protein interactions. While coarse-grained models often describe DNA as a smoothly bendable polymer, both experimental and theoretical studies indicate that mechanical stress can induce localized kinks that significantly alter its mechanical...

24. Generalized Lotka-Volterra model on sparse asymmetric graphs: local equations and Random Matrix Theory

Dr Pietro Valigi (University of Bath)

Real ecosystems, characterised by sparse and asymmetric interactions, represent highly complex disordered systems that pose a fundamental challenge for theoretical analysis. To address this, we analyse the generalised Lotka-Volterra model on sparse graphs, with and without demographic noise [1]. Drawing on the success of local closures in spin-glass dynamics [2] and combinatorial optimisation,...

23. Generative modeling of functional biosequences from artificial selection experiments

Stefano Crotti (Institut de Physique Theorique, CEA Paris-Saclay)

SELEX experiments aim at identifying short RNA strands that specifically bind to a given target molecule, through several successive rounds of \textit{in vitro} selection. This talk presents ongoing work on a mathematical model learned on SELEX data with a twofold objective: gaining insight about the biophysical mechanisms underlying the selection process, and generating novel RNA sequences...

19. How one gene wins: a two-step symmetry-breaking model of olfactory receptor choice

Martin Miranda (Helmholtz Zentrum München)

In the mammalian olfactory epithelium, each mature sensory neuron expresses a single olfactory receptor (OR) gene out of more than a thousand candidates, through a still-unknown mechanism (Monahan & Lomvardas 2015). We propose a two-step selection process: the nucleus first assembles several inter-chromosomal hubs that bring OR-specific enhancers into contact with dozens of OR genes (Monahan...

26. Impact of Material Turnover on Diffusion in Bacterial Cell Walls: A Random Walk on a Dynamic Percolation Network

Dan Shafir (New York University)

Bacteria are typically enclosed by a cell wall, a crosslinked protective structure primarily composed of peptidoglycan. In Gram-positive bacteria, unlike species such as E. coli, the cell envelope consists of a single inner membrane surrounded by a thick peptidoglycan layer, without any known dedicated transport channels. As a result, it remains an open question how the cell wall still permits...

130. Impact of Material Turnover on Diffusion in Bacterial Cell Walls: A Random Walk on a Dynamic Percolation Network

Dan Shafir

Talk

115. In search of the Hot-Spots and of the Communication Network of the Cellular Prion Protein using Information-Theoretical Measures

Alessia Guadagnin Pattaro (Istituto Nazionale di Fisica Nucleare)

The cellular prion protein (PrP^C) is mostly expressed in the brain and in the central nervous system as a structure with a disordered region and a globular part, but it has no clear role in the organisms in which it is present. For reasons that are still unknown, PrP^C spontaneously converts to its misfolded counterpart PrP^Sc, which accumulates in tissues and...

127. Integrated Computational Framework for Protein–Protein Interaction Characterization: From Binding Site Identification to Docking Evaluation

Edoardo Milanetti

Protein–protein interactions are fundamental to cellular function and represent key targets for therapeutic design, including antibodies and antibody mimetics. However, accurate prediction of binding interfaces and docking conformations remains a major challenge in computational structural biology.

A computational framework for the characterization of biomolecular recognition is presented,...

43. Invited talk

Paolo De Los Rios (EPFL, Lausanne)

Invited talk

55. Invited talk

Fernanda Pinheiro

105. L. Ferretti

Luca Ferretti (University of Oxford)

125. Leveraging Single-Cell Analysis and Trajectory Inference to Dissect Phenotypic Heterogeneity in Colorectal Cancer Organoids

Letizia Pizzini (Università degli Studi di Torino)

The capacity of tumor cells to deviate from standard differentiation programs and adopt abnormal, unregulated developmental trajectories represents a key dynamic feature of cancer progression. In colorectal cancer (CRC), the intrinsic phenotypic heterogeneity characteristic of the normal intestinal epithelium is partially preserved, while stem cell dynamics, mirroring features of native...

108. Linking complex microbial interactions and dysbiosis through a disordered Lotka–Volterra model

Samir Suweis (Università di Padova)

The rapid advancement of environmental sequencing technologies, such as metagenomics, has significantly enhanced our ability to study microbial communities. The eubiotic composition of these communities is crucial for maintaining ecological functions and host health. Species diversity is only one facet of a healthy community’s organization; together with abundance distributions and interaction...

15. Matrix-Product Belief Propagation for continuous-state-space variables

Federico Florio (Politecnico di Torino)

Computation of observables in discrete stochastic, possibly conditioned, dynamics over large sparse networks is at the basis of a myriad of applications. The Matrix-Product Belief Propagation method allows a semi-analytical estimation of such observables in tree-like networks with a controlled error that depends on the bond size, that is the dimension of the employed square matrices. Its...

107. Mechano-chemistry of C. Elegans elongation and how to infer forces in vivo

Silvia Grigolon (Laboratoire Jean Perrin (CNRS & Sorbonne Université))

A key challenge in development is understanding how complex organisms physically coordinate the morphogenesis of multiple tissues. Here, using biophysical approaches, we investigate how muscles under the epidermis specifically stimulate the extension of anterior-posterior (AP)-oriented epidermal adherens junctions during late C. elegans embryonic elongation. First, light-sheet imaging shows...

119. MesoMem: A mesoscale membrane model based on an additive potential

PIETRO SILLANO (TU Delft)

Bridging the gap between atomistic detail and continuum mechanics remains a central challenge in modeling mesoscopic biological membranes. This regime governs key processes such as membrane reshaping and protein-induced deformation, where the interplay between molecular features and mechanical response is crucial.

In this talk, I introduce MesoMem: a solvent-free, one-particle-thick,...

14. Modeling Protein Sequence Evolution as an Ornstein-Uhlenbeck Process in a Latent Space

Matteo De Leonardis (Politecnico di Torino)

High-throughput directed evolution produces longitudinal sequence libraries that are ideal for probing local fitness neighborhoods but often underpowered for global inference tasks such as contact prediction. We present an unsupervised generative model that integrates directed-evolution sequencing time series with natural homologs. We project sequences into a low-dimensional latent space...

6. Multi-Omics Topic Modeling for Cancer Subtypes

Filippo Valle (Istituto Nazionale di Fisica Nucleare)

The integration of transcriptional data with post-transcriptional regulatory layers, such as microRNA-mediated processes, is critical for identifying driver genes and characterizing subtypes in heterogeneous diseases like cancer. Here, we present a topic modeling approach based on a hierarchical stochastic block model, designed to integrate diverse multi-omics datasets. We applied this method...

9. Navigating the attractor landscape of single cells

Federico Bocci (Radboud University)

Modern single cell sequencing technologies enable us to probe cellular processes at unprecedented resolution, while introducing new theoretical challenges. A major difficulty lies in constructing dynamical models of cell behavior, as these technologies capture only a single snapshot of a cell's state, thereby preventing the observation of temporal dynamics. In this talk, I will discuss how we...

38. NON-EQUILIBRIUM THERMODYNAMICS OF PULSATING ACTIVE MATTER

Mr Michele Antonioli (University of Luxemburg)

The cardiac tissue shows deformation patterns made of spiral defects as a precursor of
cardiac arrest [1]. Such patterns are captured by pulsating active matter (PAM), which
considers particles that independently change their size by an active pulsation mechanism
that drives the system out-of-equilibrium; the competition between steric repulsion and local
synchronization allows for a...

12. Optimal Maturation Protocols for High-Affinity Antibody Targets

Marian Huot (ENS Paris)

Affinity maturation is a stochastic evolutionary process allowing the adaptive immune system to produce B-cells capable of recognizing antigenic molecules. One of the main factors influencing the quality of the maturation outcome, quantified by the affinity of the produced antibodies to the antigen, is the time-course of antigen availability. We introduce a stochastic model for affinity...

27. Optimal sensing in confined environments

Laeschkir Würthner (EMBL Heidelberg)

Sensing and inferring concentrations in the environment is a relevant task for various life-like behaviors ranging from efficient navigation to cell-cell communication. Seminal work by Berg and Purcell focusing on bacterial chemotaxis demonstrated that the precision with which concentrations can be sensed by bacteria is fundamentally limited by molecular counting noise. Interestingly, as shown...

34. Persistence-driven enhancement of enzyme diffusion

Giuliano Migliorini (Università di Padova)

In the past fifteen years, several experiments have reported an increase in the diffusion of catalytically active enzymes compared to their passive state in the absence of substrate. While these observations remain debated and appear to depend on the measurement technique, they have stimulated significant theoretical interest due to their potential biological and physical implications.

Most...

116. Polymer Physics Approach to ecDNA folding

Matteo Olimpo (Istituto Nazionale di Fisica Nucleare)

Extrachromosomal DNA (ecDNA) drives oncogene amplification through complex structural rearrangements that radically alter 3D chromatin topology. Here, we introduce a physical framework to predict the de novo 3D architecture of ecDNA in silico. By modeling DNA as a polymer driven to fold by interacting molecules (binders), we utilize the PRISMR machine-learning algorithm to infer the...

124. Predicting the 3D cancer genome architecture via polymer physics

Ciro Di Carluccio (Istituto Nazionale di Fisica Nucleare & Università di Napoli Federico II)

Recent literature increasingly highlights the crucial role of non-coding alterations in oncogenesis. In particular, structural variants (SVs) can drastically reorganize the three-dimensional architecture of the genome, leading to phenomena such as enhancer hijacking and the reorganization of chromatin domains. Theoretical models of chromosome folding are emerging as great tools to...

110. Resource allocation strategies behind rate-yield phenotypes in E.coli

Valentina Baldazzi (INRAE/Inria, Sophia-Antipolis, France)

Microbial growth consists of the conversion of nutrients from the environment into biomass and small energy cofactors (ATP, NADH, NADPH, ...) driving biomass synthesis forward. Two macroscopic criteria for characterizing microbial growth are growth rate and growth yield. The former refers to the rate of conversion of substrate into biomass, and the latter to the efficiency of the process, that...

16. RNA Mamba: a selective state space model trained on all RNA families

Giovanni Peinetti (Politecnico di Torino/ Sorbonne Université)

We introduce RNA Mamba, a generative selective state space model trained jointly on thousands of RNA families from the RFAM dataset. Mamba state space models are an alternative to Transformers, offering linear scaling with sequence length and the ability to process long-range dependencies efficiently. We incorporate structural information into the model using a structural tokenization scheme...

31. Sparse generative models of protein sequences sample larger spaces at comparable experimental success rates

Roberto Netti (Sorbonne Université)

Boltzmann Machines trained on evolutionary sequence data have emerged as a powerful paradigm for the data-driven design of artificial proteins. However, the relationship between model architecture, specifically parameter density, and experimental performance remains poorly understood. Here, we investigate this relationship using the Chorismate Mutase enzyme family as a model system. We compare...

129. Steering Sequence Generation in Protein Language Models through Iterative Lookback Monte Carlo Sampling

Francesco Calvanese

20. Symmetry breaking and avalanche shapes in modular networks

Antonio De Candia (Istituto Nazionale di Fisica Nucleare)

Experimental evidence suggests that the healthy brain operates near a critical regime, characterized by scale-free neuronal avalanches.
Recent research has increasingly focused on the mean temporal profiles of neuronal avalanches, as a more stringent and reliable test for criticality. Scaling arguments predict that, when appropriately rescaled, the mean temporal profiles of avalanches of...

118. Temperature Increases The Target Size Of Compensatory Evolution

Moulikta Sanjeev

Cells under stress undergo compensatory evolution, and often manage to restore growth. Experimental evolution experiments show that the acquisition of new functions is rare. More often, compensatory mutations take place via loss of function. Some loss-of-function mutations manifest only at high temperature. Hence, we asked whether high temperature favours compensatory evolution by increasing...

36. Temporal Organization of Neuronal Avalanches Constrained by Structural Connectivity in MEG

Gianmarco Cafaro (Istituto Nazionale di Fisica Nucleare Scientific Institute IRCCS E.Medea, Epilepsy and Clinical Neurophysiology Unit, Conegliano (TV), Italy) Department of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy Institut de Neurosciences des Systèmes (INS), INSERM, Aix-­ Marseille Universitè, Marseille, France)

The study of neuronal activity through electrophysiological recordings provides a framework to investigate brain function and how biological alterations may influence disease onset. Different analytical approaches across multiple brain scales (single neurons, neural networks, neural mass, and whole-brain activity) yield distinct biomarkers, offering insight into where and how system-level...

13. Towards co-evolution-aware ancestral sequence reconstruction: beyond site-independent models

Alya Zeinaty (CQSB, Sorbonne Université & Chimera, Sapienza Università)

Ancestral Sequence Reconstruction (ASR) is a major tool to uncover the mechanisms that shape molecular evolution and protein function.
Concretely, ASR leverages dynamic programming and computational strategies to infer ancient phenotypes of extant protein and RNA families.
However, most state-of-the-art ASR algorithms rely on an oversimplified assumption of site-independence. This...

25. Uncoupling density- and adhesion-driven rigidity transitions in embryonic tissues

Elisa Floris (University of Graz)

Organism development occurs through sequences of astonishingly precise spatiotemporal changes, along which embryonic tissues switch between fluid- and solid-like states, arising from non-linear interactions among cellular constituents. In this context, tissue fluidization observed in vivo in zebrafish embryos was interpreted, within the framework of rigidity percolation, as a rigid-to-floppy...

37. Understanding Ridge Regression for Antibody-Antigen Binding Inference with Random Matrix Theory

Alessandro Corso (Università di Padova)

Predicting antibody-antigen binding affinity from sequence data is a central challenge in computational immunology and virology. Linear models trained on deep mutational scanning (DMS) experiments provide a tractable approximation, but their generalization performance depends strongly on data structure, dimensionality, and regularization. Here, we develop an analytical framework to...

11. Universal diversity scaling in component systems, from proteomes to large language models

Andrea Mazzolini (Istituto Nazionale di Fisica Nucleare)

The diversity of components and functions in complex systems is at the basis of the system's well-being and resilience, with prominent examples in ecology, genomics, or technological systems. A hallmark of the system's diversity is Heaps’ law, which is the sub-linear growth of the number of distinct components in a modular system, i.e., the diversity, with its size. Its emergence is widespread...

35. What does the intrinsic dimension of single-cell transcriptomes actually measure?

Leonardo Agasso (Istituto Nazionale di Fisica Nucleare)

The intrinsic dimension (ID) of gene expression profiles has recently been proposed as a geometric potency score for scRNA-seq data. We test what fraction of this signal reflects genuine manifold geometry versus marginal statistics of gene expression, by preserving per-gene expression distributions while destroying co-expression structure. Across many differentiation lineages, the ID drop by...

121. Will a time-varying complex system be stable?

Christian Grilletta (Università di Padova)

Ecological communities are theoretically predicted to be unstable upon crossing a critical threshold of species diversity, as first shown by May. Yet, natural ecosystems exhibit remarkable stability, suggesting the presence of additional stabilizing mechanisms. While the diversity-stability relation is typically assessed assuming fixed interactions, real ecosystems evolve in intrinsically...