Publications

@article{Kretsch2025,

title = {Blind Prediction of Complex Water and Ion Ensembles Around                    <scp>RNA</scp>                    in                    <scp>CASP16</scp>},

author = {Rachael C. Kretsch and Elisa Posani and Eugene F. Baulin and Janusz M. Bujnicki and Giovanni Bussi and Thomas E. Cheatham and Shi‐Jie Chen and Arne Elofsson and Masoud Amiri Farsani and Olivia N. Fisher and M. Michael Gromiha and Ayush Gupta and Michiaki Hamada and K. Harini and Gang Hu and David Huang and Junichi Iwakiri and Anika Jain and Yuki Kagaya and Daisuke Kihara and Sebastian Kmiecik and Sowmya Ramaswamy Krishnan and Ikuo Kurisaki and Olivier Languin‐Cattoën and Jun Li and Shanshan Li and Karim Malekzadeh and Tsukasa Nakamura and Wentao Ni and Chandran Nithin and Michael Z. Palo and Joon Hong Park and Smita P. Pilla and Simón Poblete and Fabrizio Pucci and Pranav Punuru and Anouka Saha and Kengo Sato and Ambuj Srivastava and Genki Terashi and Emilia Tugolukova and Jacob Verburgt and Qiqige Wuyun and Gül H. Zerze and Kaiming Zhang and Sicheng Zhang and Wei Zheng and Yuanzhe Zhou and Wah Chiu and David A. Case and Rhiju Das},

doi = {10.1002/prot.70079},

issn = {1097-0134},

year  = {2026},

date = {2026-01-00},

urldate = {2026-01-00},

journal = {Proteins},

volume = {94},

number = {1},

pages = {381--402},

publisher = {Wiley},

abstract = {<jats:title>ABSTRACT</jats:title>

                  <jats:p>

                    Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo‐EM densities observed around the

                    <jats:italic>Tetrahymena</jats:italic>

                    ribozyme at 2.2–2.3 Å resolution, collected through target R1260 in the CASP16 competition. Twenty‐six groups participated in this solvation “cryo‐ensemble” prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo‐EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo‐EM densities using Pearson correlation, Spearman correlation, mutual information, and precision‐recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo‐EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo‐EM maps. We propose that further community‐wide blind challenges can drive and evaluate progress in modeling water, ions, and other previously hidden components of biomolecular systems.

                  </jats:p>},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{qmv9-1czv,

title = {Configurational entropy of random trees},

author = {Pieter H. W. Hoek and Angelo Rosa and Ralf Everaers},

url = {https://link.aps.org/doi/10.1103/qmv9-1czv},

doi = {10.1103/qmv9-1czv},

year  = {2025},

date = {2025-12-01},

urldate = {2025-12-01},

journal = {Phys. Rev. E},

volume = {112},

issue = {6},

pages = {065405},

publisher = {American Physical Society},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Posani2025,

title = {Ensemble refinement of mismodeled cryo-EM RNA structures using all-atom simulations},

author = {Elisa Posani and Pavel Janoš and Daniel Haack and Navtej Toor and Massimiliano Bonomi and Alessandra Magistrato and Giovanni Bussi},

doi = {10.1038/s41467-025-59769-0},

issn = {2041-1723},

year  = {2025},

date = {2025-12-00},

journal = {Nat Commun},

volume = {16},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Marcato:2025aa,

title = {Entropy of self-avoiding branching polymers: Mean-field theory and Monte Carlo simulations},

author = {Davide Marcato and Achille Giacometti and Amos Maritan and Angelo Rosa},

url = {https://doi.org/10.1063/5.0287899},

doi = {10.1063/5.0287899},

isbn = {0021-9606},

year  = {2025},

date = {2025-10-01},

urldate = {2025-10-01},

journal = {The Journal of Chemical Physics},

volume = {163},

number = {14},

pages = {141101},

abstract = {We study the statistics of branching polymers with excluded-volume interactions, by modeling them as single self-avoiding trees on a generic regular periodic lattice with coordination number q. Each lattice site can be occupied at most by one tree node, and the fraction of occupied sites can vary from dilute to dense conditions. By adopting the statistics of rooted-directed trees as a proxy for that of undirected trees without internal loops and by an exact mapping of the model into a field theory, we compute the entropy and the mean number of branch nodes within a mean-field approximation and in the thermodynamic limit. In particular, we find that the mean number of branch nodes is independent of both the lattice details and the lattice occupation, depending only on the associated chemical potential. Monte Carlo simulations in d = 2, 3, 4 provide evidence of the remarkable accuracy of the mean-field theory, more accurate for higher dimensions.},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{gy1p-4256,

title = {bioSBM: A Random Graph Model to Integrate Epigenomic Data in Chromatin Structure Prediction},

author = {Alex Chen Yi Zhang and Angelo Rosa and Guido Sanguinetti},

url = {https://link.aps.org/doi/10.1103/gy1p-4256},

doi = {10.1103/gy1p-4256},

year  = {2025},

date = {2025-10-01},

urldate = {2025-10-01},

journal = {PRX Life},

volume = {3},

issue = {4},

pages = {043006},

publisher = {American Physical Society},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Mizrahi2025,

title = {Evaluation of novel computational methods to identify RNA-binding protein footprints from structural data},

author = {Orel Mizrahi and Meredith Corley and Ori Feldman and Thorben Fröhlking and Lei Sun and Alison Ziesel and Maciej Antczak and Mattia Bernetti and Shaimae I. Elhajjajy and Wenze Huang and Grady G. Nguyen and Samuel S. Park and Raul I. Perez Martell and Luke Trinity and Kui Xu and Tomasz Zok and Giovanni Bussi and Hosna Jabbari and Yaron Orenstein and Sharon Aviran and Michelle M. Meyer and Gene W. Yeo},

doi = {10.1261/rna.080215.124},

issn = {1469-9001},

year  = {2025},

date = {2025-08-00},

journal = {RNA},

volume = {31},

number = {8},

pages = {1103--1124},

publisher = {Cold Spring Harbor Laboratory},

abstract = {RNA-binding proteins (RBP) play diverse roles in mRNA processing and function. However, from thousands of RBPs encoded in the human genome, a detailed molecular understanding of their interactions with RNA is available only for a small fraction. In most cases, our knowledge of the combination of RNA sequence and structure required for specific RBP binding is insufficient for accurately predicting binding sites transcriptome-wide. In this context, the rapidly expanding collection of transcriptomic data sets that map distinct, yet intertwined posttranscriptional marks, such as RNA structure and RBP binding, presents an opportunity for integrative analysis to better characterize RBP binding. A grand challenge faced by our community is that relatively little information on the secondary structure context within and near RBP-binding sites has been gleaned from integrating such data sets, partially due to lack of suitable computational methods. To engage scientists from diverse backgrounds in addressing this gap, the RNA Society organized the RBP Footprint Grand Challenge in 2021, an international community effort to develop new methods or leverage existing ones for predicting RBP-binding sites through analysis of a growing volume of sequence, structure, and binding data and to experimentally validate select predictions. Here, we report the initiative, analyses, and methods developed by the participants, validation results, and five new in vivo binding data sets generated for validation. We hope our work will inspire additional innovation in computational methods, further utilization of available data resources, and future endeavors to engage the community in collaborating toward closing other critical data-analysis gaps.},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Müller-Hermes2025,

title = {Unique conformational dynamics and protein recognition of A-to-I hyper-edited dsRNA},

author = {Christoph Müller-Hermes and Valerio Piomponi and Stefan Hilber and Sam Asami and Christoph Kreutz and Giovanni Bussi and Michael Sattler},

doi = {10.1093/nar/gkaf550},

issn = {1362-4962},

year  = {2025},

date = {2025-06-20},

volume = {53},

number = {12},

publisher = {Oxford University Press (OUP)},

abstract = {Abstract

               Adenosine-to-inosine (A-to-I) editing is a highly abundant modification of double-stranded RNA (dsRNA) and plays an important role in posttranscriptional gene regulation. Editing of multiple inosines by the ADAR1 enzyme leads to A-to-I hyper-editing of non-coding dsRNA, such as 3′UTRs, transposable elements, or foreign pathogenic RNAs, and is implicated in immune response and human diseases including cancer. The structural consequences of hyper-editing and its role in protein binding are poorly understood. Here, we combine solution nuclear magnetic resonance spectroscopy (NMR), biophysical methods such as small-angle X-ray scattering, and molecular dynamics simulations to study the sequence-dependent effects on conformation and dynamics of A-to-I hyper-editing for a 20-mer dsRNA and recognition of such RNAs by Endonuclease V. By comparing non-edited, single-edited, and hyper-edited dsRNA, we identify unique conformational features and extensive dynamics associated with hyper-editing, resulting in significantly increased base-pair opening. Hyper-edited dsRNA is more extended and adopts a highly dynamic ensemble of canonical and non-canonical conformations, which lead to preferential binding by Endonuclease V. Our integrated experimental and computational analysis identifies unique structural and dynamic features that are likely linked to specific protein recognition and the unique biological consequences of hyper-editing.},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Gilardoni2025,

title = {MDRefine: A Python package for refining molecular dynamics trajectories with experimental data},

author = {Ivan Gilardoni and Valerio Piomponi and Thorben Fröhlking and Giovanni Bussi},

doi = {10.1063/5.0256841},

issn = {1089-7690},

year  = {2025},

date = {2025-05-21},

volume = {162},

number = {19},

publisher = {AIP Publishing},

abstract = {Molecular dynamics (MD) simulations play a crucial role in resolving the underlying conformational dynamics of molecular systems. However, their capability to correctly reproduce and predict dynamics in agreement with experiments is limited by the accuracy of the force-field model. This capability can be improved by refining the structural ensembles or the force-field parameters. Furthermore, discrepancies with experimental data can be due to imprecise forward models, namely, functions mapping simulated structures to experimental observables. Here, we introduce MDRefine, a Python package aimed at implementing the refinement of the ensemble, the force field, and/or the forward model by comparing MD-generated trajectories with the experimental data. The software consists of several tools that can be employed separately from each other or combined together in different ways, providing a seamless interpolation between these three different types of refinement. We use some benchmark cases to show that the combined approach is superior to separately applied refinements. MDRefine has been released as an open-source package under the LGPLv2+ license. Source code, documentation, and examples are available at https://pypi.org/project/MDRefine and https://github.com/bussilab/MDRefine.},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Boccalini2025,

title = {Exploring RNA destabilization mechanisms in biomolecular condensates through atomistic simulations},

author = {Matteo Boccalini and Yelyzaveta Berezovska and Giovanni Bussi and Matteo Paloni and Alessandro Barducci},

doi = {10.1073/pnas.2425261122},

issn = {1091-6490},

year  = {2025},

date = {2025-04-15},

journal = {Proc. Natl. Acad. Sci. U.S.A.},

volume = {122},

number = {15},

publisher = {Proceedings of the National Academy of Sciences},

abstract = {Biomolecular condensates are currently recognized to play a key role in organizing cellular space and in orchestrating biochemical processes. Despite an increasing interest in characterizing their internal organization at the molecular scale, not much is known about how the densely crowded environment within these condensates affects the structural properties of recruited macromolecules. Here, we adopted explicit-solvent all-atom simulations based on a combination of enhanced sampling approaches to investigate how the conformational ensemble of an RNA hairpin is reshaped in a highly concentrated peptide solution that mimics the interior of a biomolecular condensate. Our simulations indicate that RNA structure is greatly perturbed by this distinctive physico-chemical environment, which weakens RNA secondary structure and promotes extended nonnative conformations. The resulting high-resolution picture reveals that RNA unfolding is driven by the effective solvation of nucleobases through hydrogen bonding and stacking interactions with surrounding peptides. This solvent effect can be modulated by the amino acid composition of the model condensate as proven by the differential RNA behavior observed in the case of arginine-rich and lysine-rich peptides.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Silva2025,

title = {Characterizing RNA Oligomers Using Stochastic Titration Constant-pH Metadynamics Simulations},

author = {Tomás F. D. Silva and Giovanni Bussi},

doi = {10.1021/acs.jcim.4c02185},

issn = {1549-960X},

year  = {2025},

date = {2025-04-14},

journal = {J. Chem. Inf. Model.},

volume = {65},

number = {7},

pages = {3568--3580},

publisher = {American Chemical Society (ACS)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Amaro2025,

title = {The need to implement FAIR principles in biomolecular simulations},

author = {Rommie E. Amaro and Johan Åqvist and Ivet Bahar and Federica Battistini and Adam Bellaiche and Daniel Beltran and Philip C. Biggin and Massimiliano Bonomi and Gregory R. Bowman and Richard A. Bryce and Giovanni Bussi and Paolo Carloni and David A. Case and Andrea Cavalli and Chia-En A. Chang and Thomas E. Cheatham and Margaret S. Cheung and Christophe Chipot and Lillian T. Chong and Preeti Choudhary and G. Andres Cisneros and Cecilia Clementi and Rosana Collepardo-Guevara and Peter Coveney and Roberto Covino and T. Daniel Crawford and Matteo Dal Peraro and Bert L. de Groot and Lucie Delemotte and Marco De Vivo and Jonathan W. Essex and Franca Fraternali and Jiali Gao and Josep Ll. Gelpí and Francesco L. Gervasio and Fernando D. González-Nilo and Helmut Grubmüller and Marina G. Guenza and Horacio V. Guzman and Sarah Harris and Teresa Head-Gordon and Rigoberto Hernandez and Adam Hospital and Niu Huang and Xuhui Huang and Gerhard Hummer and Javier Iglesias-Fernández and Jan H. Jensen and Shantenu Jha and Wanting Jiao and William L. Jorgensen and Shina C. L. Kamerlin and Syma Khalid and Charles Laughton and Michael Levitt and Vittorio Limongelli and Erik Lindahl and Kresten Lindorff-Larsen and Sharon Loverde and Magnus Lundborg and Yun L. Luo and F. Javier Luque and Charlotte I. Lynch and Alexander D. MacKerell and Alessandra Magistrato and Siewert J. Marrink and Hugh Martin and J. Andrew McCammon and Kenneth Merz and Vicent Moliner and Adrian J. Mulholland and Sohail Murad and Athi N. Naganathan and Shikha Nangia and Frank Noe and Agnes Noy and Julianna Oláh and Megan L. O’Mara and Mary Jo Ondrechen and Jose N. Onuchic and Alexey Onufriev and Sílvia Osuna and Giulia Palermo and Anna R. Panchenko and Sergio Pantano and Carol Parish and Michele Parrinello and Alberto Perez and Tomas Perez-Acle and Juan R. Perilla and B. Montgomery Pettitt and Adriana Pietropaolo and Jean-Philip Piquemal and Adolfo B. Poma and Matej Praprotnik and Maria J. Ramos and Pengyu Ren and Nathalie Reuter and Adrian Roitberg and Edina Rosta and Carme Rovira and Benoit Roux and Ursula Rothlisberger and Karissa Y. Sanbonmatsu and Tamar Schlick and Alexey K. Shaytan and Carlos Simmerling and Jeremy C. Smith and Yuji Sugita and Katarzyna Świderek and Makoto Taiji and Peng Tao and D. Peter Tieleman and Irina G. Tikhonova and Julian Tirado-Rives and Iñaki Tuñón and Marc W. van der Kamp and David van der Spoel and Sameer Velankar and Gregory A. Voth and Rebecca Wade and Ariel Warshel and Valerie Vaissier Welborn and Stacey D. Wetmore and Travis J. Wheeler and Chung F. Wong and Lee-Wei Yang and Martin Zacharias and Modesto Orozco},

doi = {10.1038/s41592-025-02635-0},

issn = {1548-7105},

year  = {2025},

date = {2025-04-00},

journal = {Nat Methods},

volume = {22},

number = {4},

pages = {641--645},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DiMarco2025,

title = {All-Atom Simulations Elucidate the Molecular Mechanism Underlying RNA–Membrane Interactions},

author = {Salvatore Di Marco and Jana Aupič and Giovanni Bussi and Alessandra Magistrato},

doi = {10.1021/acs.nanolett.5c01254},

issn = {1530-6992},

year  = {2025},

date = {2025-03-19},

journal = {Nano Lett.},

volume = {25},

number = {11},

pages = {4628--4635},

publisher = {American Chemical Society (ACS)},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{Tribello2025,

title = {PLUMED Tutorials: A collaborative, community-driven learning ecosystem},

author = {Gareth A. Tribello and Massimiliano Bonomi and Giovanni Bussi and Carlo Camilloni and Blake I. Armstrong and Andrea Arsiccio and Simone Aureli and Federico Ballabio and Mattia Bernetti and Luigi Bonati and Samuel G. H. Brookes and Z. Faidon Brotzakis and Riccardo Capelli and Michele Ceriotti and Kam-Tung Chan and Pilar Cossio and Siva Dasetty and Davide Donadio and Bernd Ensing and Andrew L. Ferguson and Guillaume Fraux and Julian D. Gale and Francesco Luigi Gervasio and Toni Giorgino and Nicholas S. M. Herringer and Glen M. Hocky and Samuel E. Hoff and Michele Invernizzi and Olivier Languin-Cattoën and Vanessa Leone and Vittorio Limongelli and Olga Lopez-Acevedo and Fabrizio Marinelli and Pedro Febrer Martinez and Matteo Masetti and Shams Mehdi and Angelos Michaelides and Mhd Hussein Murtada and Michele Parrinello and Pablo M. Piaggi and Adriana Pietropaolo and Fabio Pietrucci and Silvio Pipolo and Claire Pritchard and Paolo Raiteri and Stefano Raniolo and Daniele Rapetti and Valerio Rizzi and Jakub Rydzewski and Matteo Salvalaglio and Christoph Schran and Aniruddha Seal and Armin Shayesteh Zadeh and Tomás F. D. Silva and Vojtěch Spiwok and Guillaume Stirnemann and Daniel Sucerquia and Pratyush Tiwary and Omar Valsson and Michele Vendruscolo and Gregory A. Voth and Andrew D. White and Jiangbo Wu},

doi = {10.1063/5.0251501},

issn = {1089-7690},

year  = {2025},

date = {2025-03-07},

urldate = {2025-03-07},

journal = {JOURNAL OF CHEMICAL PHYSICS},

volume = {162},

number = {9},

pages = {092501},

publisher = {AIP Publishing},

abstract = {<jats:p>In computational physics, chemistry, and biology, the implementation of new techniques in shared and open-source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited in reach and comprehensiveness. Furthermore, while the COVID-19 pandemic highlighted the benefits of online training, traditional online tutorials can quickly become outdated and may not cover all the software’s functionalities. To address these issues, here we introduce “PLUMED Tutorials,” a collaborative model for developing, sharing, and updating online tutorials. This initiative utilizes repository management and continuous integration to ensure compatibility with software updates. Moreover, the tutorials are interconnected to form a structured learning path and are enriched with automatic annotations to provide broader context. This paper illustrates the development, features, and advantages of PLUMED Tutorials, aiming to foster an open community for creating and sharing educational resources.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{wild2025automatic,

title = {Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance},

author = {Romina Wild and Felix Wodaczek and Vittorio Del Tatto and Bingqing Cheng and Alessandro Laio},

year  = {2025},

date = {2025-01-01},

journal = {Nature Communications},

volume = {16},

number = {1},

pages = {270},

publisher = {Nature Publishing Group UK London},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ubertini:2025aa,

title = {Ring polymers in two-dimensional melts double-fold around randomly branching ``primitive shapes''},

author = {Mattia A. Ubertini and Angelo Rosa},

url = {http://dx.doi.org/10.1039/D5SM00947B},

doi = {10.1039/D5SM00947B},

isbn = {1744-683X},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Soft Matter},

volume = {21},

number = {45},

pages = {8711–8723},

publisher = {The Royal Society of Chemistry},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{jusuf2025genome,

title = {Genome-wide absolute quantification of chromatin looping},

author = {James M Jusuf and Simon Grosse-Holz and Michele Gabriele and Pia Mach and Ilya M Flyamer and Christoph Zechner and Luca Giorgetti and Leonid A Mirny and Anders S Hansen},

year  = {2025},

date = {2025-01-01},

journal = {bioRxiv},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{moor2025state,

title = {State-versus Reaction-Based Information Processing in Biochemical Networks},

author = {Anne-Lena Moor and Age Tjalma and Manuel Reinhardt and Pieter Rein ten Wolde and Christoph Zechner},

year  = {2025},

date = {2025-01-01},

journal = {arXiv preprint arXiv:2505.13373},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{reinhardt2025mutual,

title = {Mutual Information Rate–Linear Noise Approximation and Exact Computation},

author = {Manuel Reinhardt and Age J Tjalma and Anne-Lena Moor and Christoph Zechner and Pieter Rein ten Wolde},

year  = {2025},

date = {2025-01-01},

journal = {arXiv preprint arXiv:2508.21220},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{janevcek2025computer,

title = {Computer Folding of Parallel DNA G-Quadruplex: Hitchhiker's Guide to the Conformational Space},

author = {Michal Janeček and Petra Kührová and Vojtěch Mlýnský and Petr Stadlbauer and Michal Otyepka and Giovanni Bussi and Jiří Šponer and Pavel Banáš},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Journal of computational chemistry},

volume = {46},

number = {1},

pages = {e27535},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{micheletti2024topology,

title = {Topology-Based Detection and Tracking of Deadlocks Reveal Aging of Active Ring Melts},

author = {Cristian Micheletti and Iurii Chubak and Enzo Orlandini and Jan Smrek},

year  = {2024},

date = {2024-01-01},

journal = {ACS Macro Letters},

volume = {13},

number = {2},

pages = {124–129},

publisher = {American Chemical Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{caraglio2024unraveling,

title = {Unraveling the Influence of Topology and Spatial Confinement on Equilibrium and Relaxation Properties of Interlocked Ring Polymers},

author = {Michele Caraglio and Cristian Micheletti and Enzo Orlandini},

year  = {2024},

date = {2024-01-01},

journal = {Macromolecules},

volume = {57},

number = {7},

pages = {3223–3233},

publisher = {American Chemical Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tagliabue2024effect,

title = {Effect of Counterion Size on Knotted Polyelectrolyte Conformations},

author = {Andrea Tagliabue and Cristian Micheletti and Massimo Mella},

year  = {2024},

date = {2024-01-01},

journal = {The Journal of Physical Chemistry B},

volume = {128},

number = {17},

pages = {4183–4194},

publisher = {American Chemical Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{luengo2024shape,

title = {Shape and Size Tunability of Sheets of Interlocked Ring Copolymers},

author = {Juan Luengo-Márquez and Salvatore Assenza and Cristian Micheletti},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2406.13561},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{suma2024unzipping,

title = {Unzipping of knotted DNA via nanopore translocation},

author = {Antonio Suma and Cristian Micheletti},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2407.11567},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zheng2024knots,

title = {When Knots are Plectonemes},

author = {Fei Zheng and Antonio Suma and Christopher Maffeo and Kaikai Chen and Mohammed Alawami and Jingjie Sha and Aleksei Aksimentiev and Cristian Micheletti and Ulrich F Keyser},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2407.16290},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{panizza2024protein,

title = {Protein Design by Integrating Machine Learning and Quantum-Encoded Optimization},

author = {Veronica Panizza and Philipp Hauke and Cristian Micheletti and Pietro Faccioli},

year  = {2024},

date = {2024-01-01},

journal = {PRX Life},

volume = {2},

number = {4},

pages = {043012},

publisher = {American Physical Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gasparotto2024mapping,

title = {Mapping Cryptic Phosphorylation Sites in the Human Proteome},

author = {Dino Gasparotto and Annarita Zanon and Valerio Bonaldo and Elisa Marchiori and Massimo Casagranda and Erika Di Domenico and Laura Copat and Tommaso Fortunato Asquini and Marta Rigoli and Sirio Vittorio Feltrin and others},

year  = {2024},

date = {2024-01-01},

journal = {bioRxiv},

pages = {2024–12},

publisher = {Cold Spring Harbor Laboratory},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dellostritto2024molecular,

title = {Molecular dynamics studies of knotted polymers},

author = {Mark DelloStritto and Cristian Micheletti and Michael L Klein},

year  = {2024},

date = {2024-01-01},

journal = {The Journal of Chemical Physics},

volume = {161},

number = {24},

publisher = {AIP Publishing},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zhang2024bottom,

title = {Bottom-up data integration in polymer models of chromatin organisation},

author = {Alex Chen Yi Zhang and Angelo Rosa and Guido Sanguinetti},

year  = {2024},

date = {2024-01-01},

journal = {Biophysical Journal},

volume = {123},

number = {2},

pages = {184–194},

publisher = {Cell Press},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{ubertini2024universal,

title = {Universal time and length scales of polar active polymer melts},

author = {Mattia Alberto Ubertini and Emanuele Locatelli and Angelo Rosa},

year  = {2024},

date = {2024-01-01},

journal = {ACS Macro Letters},

volume = {13},

number = {9},

pages = {1204–1210},

publisher = {American Chemical Society},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{tubiana2024topology,

title = {Topology in soft and biological matter},

author = {Luca Tubiana and Gareth P Alexander and Agnese Barbensi and Dorothy Buck and Julyan HE Cartwright and Mateusz Chwastyk and Marek Cieplak and Ivan Coluzza and Simon Čopar and David J Craik and others},

year  = {2024},

date = {2024-01-01},

journal = {Physics Reports},

volume = {1075},

pages = {1–137},

publisher = {North-Holland},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{arcangeli2024phase,

title = {Phase Behavior and Self-Assembly of Semiflexible Polymers in Poor-Solvent Solutions},

author = {Tobia Arcangeli and Tatjana S krbic and Somiealo Azote and Davide Marcato and Angelo Rosa and Jayanth R Banavar and Roberto Piazza and Amos Maritan and Achille Giacometti},

year  = {2024},

date = {2024-01-01},

journal = {Macromolecules},

volume = {57},

number = {18},

pages = {8940–8955},

publisher = {American Chemical Society},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{van2024amoeba,

title = {Amoeba Monte Carlo algorithms for random trees with controlled branching activity: Efficient trial move generation and universal dynamics},

author = {Pieter HW Hoek and Angelo Rosa and Ralf Everaers},

year  = {2024},

date = {2024-01-01},

journal = {Physical Review E},

volume = {110},

number = {4},

pages = {045312},

publisher = {American Physical Society},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{marcato2024theory,

title = {Theory of polymers in binary solvent solutions: mean-field free energy and phase behavior},

author = {Davide Marcato and Achille Giacometti and Amos Maritan and Angelo Rosa},

url = {https://doi.org/10.1103/PhysRevMaterials.8.125601},

year  = {2024},

date = {2024-01-01},

journal = {Physical Review Materials},

volume = {8},

pages = {125601},

keywords = {Student Paper},

pubstate = {published},

tppubtype = {article}

}

@article{rende2024mapping,

title = {Mapping of attention mechanisms to a generalized Potts model},

author = {Riccardo Rende and Federica Gerace and Alessandro Laio and Sebastian Goldt},

year  = {2024},

date = {2024-01-01},

journal = {Physical Review Research},

volume = {6},

number = {2},

pages = {023057},

publisher = {American Physical Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{del2024robust,

title = {Robust inference of causality in high-dimensional dynamical processes from the Information Imbalance of distance ranks},

author = {V Del Tatto and G Fortunato and D Bueti and A Laio and others},

year  = {2024},

date = {2024-01-01},

journal = {PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA},

volume = {121},

number = {19},

pages = {1–10},

publisher = {National Academy of Sciences},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{wild2024maximally,

title = {Maximally informative feature selection using Information Imbalance: Application to COVID-19 severity prediction},

author = {Romina Wild and Emanuela Sozio and Riccardo G Margiotta and Fabiana Dellai and Angela Acquasanta and Fabio Del Ben and Carlo Tascini and Francesco Curcio and Alessandro Laio},

year  = {2024},

date = {2024-01-01},

journal = {Scientific Reports},

volume = {14},

number = {1},

pages = {10744},

publisher = {Nature Publishing Group UK London},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{grafke2024metadynamics,

title = {Metadynamics for transition paths in irreversible dynamics},

author = {Tobias Grafke and Alessandro Laio},

year  = {2024},

date = {2024-01-01},

journal = {Multiscale Modeling & Simulation},

volume = {22},

number = {1},

pages = {125–141},

publisher = {Society for Industrial and Applied Mathematics University City, Philadelphia},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bernardi2024improving,

title = {Improving acute stroke assessment in non-enhanced computed tomography: automated tool for early ischemic lesion volume detection},

author = {Mara Sabina Bernardi and Alex Rodriguez and Paola Caruso and Giovanni Furlanis and Mariana Ridolfi and Gabriele Prandin and Marcello Naccarato and Alessandro Laio and Daniele Amati and Paolo Manganotti},

year  = {2024},

date = {2024-01-01},

journal = {Neurological Sciences},

pages = {1–9},

publisher = {Springer International Publishing Cham},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{springer2024unsupervised,

title = {Unsupervised detection of large-scale weather patterns in the northern hemisphere via Markov State Modelling: from blockings to teleconnections},

author = {Sebastian Springer and Alessandro Laio and Vera Melinda Galfi and Valerio Lucarini},

year  = {2024},

date = {2024-01-01},

journal = {npj Climate and Atmospheric Science},

volume = {7},

number = {1},

pages = {105},

publisher = {Nature Publishing Group UK London},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cheng2024emergence,

title = {Emergence of a High-Dimensional Abstraction Phase in Language Transformers},

author = {Emily Cheng and Diego Doimo and Corentin Kervadec and Iuri Macocco and Jade Yu and Alessandro Laio and Marco Baroni},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2405.15471},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{di2024beyond,

title = {Beyond the noise: intrinsic dimension estimation with optimal neighbourhood identification},

author = {Antonio Di Noia and Iuri Macocco and Aldo Glielmo and Alessandro Laio and Antonietta Mira},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2405.15132},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{carli2024density,

title = {Density estimation via binless multidimensional integration},

author = {Matteo Carli and Alex Rodriguez and Alessandro Laio and Aldo Glielmo},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2407.08094},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{macocco2024intrinsic,

title = {Intrinsic dimension as a multi-scale summary statistics in network modeling},

author = {Iuri Macocco and Antonietta Mira and Alessandro Laio},

year  = {2024},

date = {2024-01-01},

journal = {Scientific Reports},

volume = {14},

number = {1},

pages = {17756},

publisher = {Nature Publishing Group UK London},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gerace2024choose,

title = {How to choose the right transfer learning protocol? A qualitative analysis in a controlled set-up},

author = {Federica Gerace and Diego Doimo and Stefano Sarao Mannelli and Luca Saglietti and Alessandro Laio and others},

year  = {2024},

date = {2024-01-01},

journal = {Transactions on Machine Learning Research},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{barone2024unsupervised,

title = {Unsupervised domain classification of AlphaFold2-predicted protein structures},

author = {Federico Barone and Alessandro Laio and Marco Punta and Stefano Cozzini and Alessio Ansuini and Alberto Cazzaniga},

year  = {2024},

date = {2024-01-01},

journal = {bioRxiv},

pages = {2024–08},

publisher = {Cold Spring Harbor Laboratory},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tamagnone2024coarse,

title = {Coarse-Grained Molecular Dynamics with Normalizing Flows},

author = {Samuel Tamagnone and Alessandro Laio and Marylou Gabrié},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Chemical Theory and Computation},

volume = {20},

number = {18},

pages = {7796–7805},

publisher = {American Chemical Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rende2024distributional,

title = {A distributional simplicity bias in the learning dynamics of transformers},

author = {Riccardo Rende and Federica Gerace and Alessandro Laio and Sebastian Goldt},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2410.19637},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acevedo2024unsupervised,

title = {Unsupervised detection of semantic correlations in big data},

author = {Santiago Acevedo and Alex Rodriguez and Alessandro Laio},

year  = {2024},

date = {2024-01-01},

journal = {arXiv preprint arXiv:2411.02126},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{thiel2024sampling,

title = {Sampling globally and locally correct rna 3d structures using ernwin, spqr and experimental saxs data},

author = {Bernhard C Thiel and Giovanni Bussi and Simón Poblete and Ivo L Hofacker},

year  = {2024},

date = {2024-01-01},

journal = {Nucleic Acids Research},

pages = {gkae602},

publisher = {Oxford University Press},

keywords = {},

pubstate = {published},

tppubtype = {article}

}