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PLUMED Tutorials: a collaborative, community-driven learning ecosystem

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read PLUMED Tutorials is a collaborative infrastructure in which tutorial pages are rebuilt from contributor archives, automatically tested against the current and development versions of the PLUMED software, and interconnected through a…

desk verdict A real, useful infrastructure paper whose main overreach is calling the tutorial graph a 'structured learning path' without reporting how connected it actually is. read the letter →

arxiv 2412.03595 v1 pith:2YRRAYBL submitted 2024-11-29 physics.ed-ph physics.chem-phphysics.comp-ph

Gareth A. Tribello , Massimiliano Bonomi , Giovanni Bussi , Carlo Camilloni , Blake I. Armstrong , Andrea Arsiccio , Simone Aureli , Federico Ballabio
show 55 more authors
Mattia Bernetti Luigi Bonati Samuel G. H. Brookes Z. Faidon Brotzakis Riccardo Capelli Michele Ceriotti Kam-Tung Chan Pilar Cossio Siva Dasetty Davide Donadio Bernd Ensing Andrew L. Ferguson Guillaume Fraux Julian D. Gale Francesco Luigi Gervasio Toni Giorgino Nicholas S. M. Herringer Glen M. Hocky Samuel E. Hoff Michele Invernizzi Olivier Languin-Cattöen Vanessa Leone Vittorio Limongelli Olga Lopez-Acevedo Fabrizio Marinelli Pedro Febrer Martinez Matteo Masetti Shams Mehdi Angelos Michaelides Mhd Hussein Murtada Michele Parrinello Pablo M. Piaggi Adriana Pietropaolo Fabio Pietrucci Silvio Pipolo Claire Pritchard Paolo Raiteri Stefano Raniolo Daniele Rapetti Valerio Rizzi Jakub Rydzewski Matteo Salvalaglio Christoph Schran Aniruddha Seal Armin Shayesteh Zadeh Tomás F. D. Silva Vojtěch Spiwok Guillaume Stirnemann Daniel Sucerquia Pratyush Tiwary Omar Valsson Michele Vendruscolo Gregory A. Voth Andrew D. White Jiangbo Wu
This is my paper · ORCID
classification physics.ed-phphysics.chem-phphysics.comp-ph
keywords PLUMEDonlinetutorialscommunity-driveneducationcontinuousintegrationenhancedsamplingmoleculardynamicslearningpathopensourcesoftwaretraining
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper presents PLUMED Tutorials, an open infrastructure for developing, sharing, and updating online tutorials for the PLUMED molecular-dynamics software. The authors argue that this collaborative model overcomes three limitations of traditional training: in-person schools reach few students and are time-constrained, static online tutorials go stale as the software evolves, and manually curated material rarely covers the full range of implemented methods. In their design, tutorial files live in contributor-controlled archives, a continuous-integration build assembles the site, and every example input is automatically parsed by both the release and development versions of PLUMED so that obsolete material is flagged. Tutorials can link to one another, and a graph distilled from those links gives newcomers a suggested learning path. If the model works, it gives the community a living training resource that stays in step with the code and complements journal articles.

What carries the argument

The central mechanism is the PLUMED Tutorials build-and-render pipeline. A GitHub Actions workflow downloads contributor archives from GitHub or Zenodo and constructs a GitHub Pages site, reading NAVIGATION.md (written in GitHub markdown plus Mermaid diagram syntax) for the landing page and EMBED.yml to resolve embedded videos, external links, and links to other tutorials. The pipeline's renderer for PLUMED input files carries the argument: it parses each code block with the current release and master versions of PLUMED to produce compatibility badges, attaches keyword tooltips linked to the PLUMED manual, expands shortcut actions into their full underlying inputs, and color-codes values passed between actions. A second mechanism, the indexing step, creates a directed graph from contributor-supplied tutorial links, removes circular dependencies, applies a transitive reduction, and thereby produces a democratically determined learning path; tutorials with no incoming links simply do not appear in that graph.

What would settle it

Watch the live tutorial site across one or two PLUMED release cycles and compute the fraction of rendered input blocks showing red parse badges after each release; if that fraction stays high for months, or if the number of contributions stops growing, the claim that continuous integration keeps tutorials compatible and that the community sustains the collection would be contradicted.

Watch

Extended reading notes

Core claim

The central claim is that a software community can maintain its own training ecosystem through repository management and continuous integration rather than through centralized authorship. The authors show that PLUMED Tutorials pages are constructed automatically from zip archives contributed by any researcher; each archive contains markdown, notebooks, PDFs, videos, a NAVIGATION.md file that specifies a Mermaid diagram, and an EMBED.yml file that declares embedded and external resources. The renderer turns every PLUMED input block into an annotated, interactive object: it tests whether the current release and the master branch can parse the input, shows a green or red badge accordingly, adds hover tooltips that explain keywords and link to manual pages, expands shortcut actions to reveal their defaults and inner workings, and highlights the values passed between actions. Instead of imposing a fixed curriculum, the site lets contributors link their tutorials to others, and the indexing layer builds a directed graph from those links, removes circular dependencies, and applies a transitive reduction to suggest an order to work through the material. The authors argue this makes the collection more comprehensive than any single school, keeps it compatible with an evolving codebase, and provides students with both context and guidance.

Load-bearing premise

The ecosystem's value depends on sustained voluntary contributions and on contributors linking their tutorials to others, since unlinked tutorials drop out of the learning-path graph and the collection would otherwise go stale.

Editorial extensions

If this is right

  • Learners anywhere can work through the same material asynchronously, and instructors can assign tutorials before an in-person school so meeting time is spent on projects and discussions.
  • Because every example input is checked against the current and development versions of PLUMED, syntax changes become visible immediately as red badges, prompting updates before tutorials break silently.
  • The set of tutorials a student sees is not fixed by editors; it grows and reorganizes as contributors add or link tutorials, so the learning path is community-determined.
  • Developers can use the automatically built action and module indexes to see which features are used in tutorials and in PLUMED-NEST, and manual pages can link to live examples.
  • The same tooling renders more than 1,600 example inputs from tutorials and PLUMED-NEST, so the annotated corpus of working examples becomes a richer training resource than a manual alone.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Beyond the paper, the same pipeline could be applied to other scientific software with a well-defined input language: the combination of CI-driven parsing and manual-linked tooltips is not PLUMED-specific.
  • The compatibility badges only test whether inputs parse; a natural extension would be to run the tutorials' commands end-to-end on small systems, catching runtime and numerical breakage that parsing misses.
  • The action-usage index that accumulates from rendered inputs could become a measurable record of method adoption across the community, useful for studying how simulation techniques spread.
  • If the guidance graph were augmented with prerequisite relations inferred from action usage, the site could recommend remedial tutorials to a learner before they start a target tutorial.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. This paper presents PLUMED Tutorials, a community-driven infrastructure for developing, sharing, and updating online tutorials for the PLUMED molecular simulation package. After reviewing the limitations of past in-person PLUMED schools and static online tutorials, the authors describe the contribution workflow: contributors package markdown files, Python notebooks, PDFs, videos, and PLUMED input files in a zip archive with NAVIGATION.md and EMBED.yml files; a GitHub Actions workflow builds the site and renders each tutorial with a Mermaid navigation graph. The paper also details the automatic rendering of PLUMED input files, including parse-status badges for the current and development versions of PLUMED, hover tooltips with keyword documentation, expansion of shortcut actions, and highlighting of data passed between actions. It then describes the searchable index and a guidance graph constructed from inter-tutorial links via cycle removal and transitive reduction. The live site currently contains 47 tutorials, and the authors position the platform as a model for other scientific software communities.

Significance. The paper's concrete strengths are that the resource is public and working, the contribution and testing workflow is described in sufficient detail to be reproduced, and the automated annotation and syntax-checking features are genuinely useful for keeping training materials connected to a fast-moving code base. If the claims about the current corpus are supported, the platform would be a valuable template for community-maintained training materials in computational science. However, the paper provides no quantitative evidence for two central claims: that the 47 tutorials actually form a structured learning path, and that continuous integration ensures ongoing compatibility. It also presents no evaluation of educational effectiveness. These gaps are fixable and do not undermine the value of the infrastructure description, but they currently leave the headline claims stronger than the evidence.

major comments (3)
  1. [Indexing the tutorials] The abstract claims that the tutorials 'are interconnected to form a structured learning path,' but the only support is Fig. 5, which displays 'selected tutorials,' and the text explicitly states that tutorials without incoming links and without outgoing links do not appear in that graph. The manuscript does not report how many of the 47 tutorials are nodes in the guidance graph, how many directed edges exist after transitive reduction, or the sizes of the connected components. Without these numbers, the current corpus could consist of a small linked core and many isolated tutorials, which would make 'a structured learning path' an overstatement. Please report the graph statistics or soften the claim to describe the linking mechanism as a capability.
  2. [Linking the tutorials with the documentation] The abstract states that continuous integration is used to 'ensure compatibility with software updates,' but the described test only checks whether the current release and master branch can parse the input files (the green/red badges in Fig. 2). This verifies syntactic parseability, not that the tutorial runs correctly, produces the intended results, or remains numerically compatible. Moreover, no data are reported on how many of the 47 tutorials currently parse under both versions, so the claim of ensured compatibility is stronger than the evidence. Please either report the current pass rates and clarify the scope of the checks, or revise the wording to 'check syntactic compatibility.'
  3. [Conclusions] The paper asserts without supporting evidence that PLUMED Tutorials 'offer a more comprehensive overview of the software's functionalities' and that the tooltips and hyperlinks make it easier for students to understand and modify inputs. These are testable claims about the resource's educational value, but no learning-outcome data, user surveys, or comparison with previous tutorial formats are provided. Since the paper is submitted to a physics education venue and the abstract positions the initiative as addressing training challenges, some form of evaluation—even a small usability or learning study—would substantially strengthen the central claims. If the paper is intended as an infrastructure description rather than an efficacy study, the claims should be correspondingly hedged.
minor comments (5)
  1. [How to contribute a PLUMED Tutorial] The file name 'NA VIGATION.md' appears with a space in two places; it should read 'NAVIGATION.md'.
  2. [Acknowledgement] The phrase 'S.E.H. is founded by a Roux-Cantarini fellowship' should be 'funded by'.
  3. [Indexing the tutorials] The caption of Fig. 5 says 'Selected tutorials'; since the text describes the figure as the guidance graph for all tutorials, please state in the caption whether the figure is complete or a curated subset and how the selection was made.
  4. [Linking the tutorials with the documentation] The phrase 'how some of complex methods are constructed' should be 'how some complex methods are constructed'.
  5. [Indexing the tutorials] The sentence describing the HTML string '%20' as a separator is imprecise; it is the URL-encoding of a space. Consider rewording for clarity.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation: the paper describes a community infrastructure and constructs its learning-path graph directly from contributor links, with no fitted parameter or prediction that reduces to its input.

full rationale

PLUMED Tutorials is an infrastructure/education paper; it contains no equations, no fitted parameters, and no predictive claim from which a hidden equivalence could follow. The one constructed object, the advice graph in Fig. 5, is explicitly built from contributor-supplied links: the text states that to construct it "we use the links that contributors have included to other tutorials" and then "remove any circular dependencies and perform a transitive reduction." This is a faithful description of an implementation, not a derivation of an external pedagogical result. The paper even acknowledges the definitional boundary: a tutorial that neither links out nor is linked to "does not appear in the graph." No parameter is fitted to a subset of data and then reported as a prediction; no uniqueness theorem from the authors' prior work is invoked to rule out alternatives; and no known result is renamed as new. The community-authored, self-referential character of the paper is real, but it is an evidence-quality and potential-bias concern, not circularity under the specified patterns. The skeptic's point that the paper does not quantify how many of the 47 tutorials appear in the guidance graph is a support gap, not a logical circle. Accordingly, the circularity score is 0.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The central claim, that PLUMED Tutorials provides a sustainable, comprehensive and up-to-date training ecosystem, rests on assumptions about community participation, the reliability of external hosting services, and the validity of parse-success as a measure of tutorial quality. There are no fitted parameters or invented entities.

assumptions (3)
  • domain assumption A voluntary community will contribute and maintain tutorials over time.
    The 'community-driven' model described in the Abstract depends on sustained contributions; the indexing section shows that tutorials are only included in the suggested order graph when contributors link them.
  • domain assumption GitHub Actions, GitHub Pages, and Zenodo will remain available and suitable for the build workflow.
    The entire pipeline in 'How to contribute a PLUMED Tutorial' relies on these external, free services.
  • domain assumption The ability of PLUMED to parse an input file indicates that the tutorial is up to date and pedagogically valid.
    The green/red badges are generated from parse tests against release and master branches, as described in 'Linking the tutorials with the documentation'. This treats syntax compatibility as a proxy for tutorial correctness, which is not proven.

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Cite this review

Pith. "Pith review of PLUMED Tutorials: a collaborative, community-driven learning ecosystem." pith.science (2026). https://pith.science/paper/2YRRAYBL

@misc{pith2026241203595,
  author       = {Pith},
  title        = {Pith review of: PLUMED Tutorials: a collaborative, community-driven learning ecosystem},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2YRRAYBL}},
  note         = {Machine review of arXiv:2412.03595}
}
read the original abstract

In computational physics, chemistry, and biology, the implementation of new techniques in a 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.

Figures

Figures reproduced from arXiv: 2412.03595 by the authors.

Figure 1
Figure 1. An example of one of the graphs that show students how to work through a tutorial [PITH_FULL_IMAGE:figures/full_fig_p009_1.png] view at source ↗
Figure 2
Figure 2. An example showing how PLUMED input files are rendered when they appear on [PITH_FULL_IMAGE:figures/full_fig_p012_2.png] view at source ↗
Figure 3
Figure 3. An example of some of the advanced features of the rendered inputs that appear in [PITH_FULL_IMAGE:figures/full_fig_p014_3.png] view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: An illustration showing how the values that are passed between actions are illustrated [PITH_FULL_IMAGE:figures/full_fig_p016_4.png]
Figure 5
Figure 5. Figure 5: Selected tutorials that are available on the PLUMED Tutorials website and the order [PITH_FULL_IMAGE:figures/full_fig_p018_5.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

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Reference graph

Works this paper leans on

49 extracted references · 46 canonical work pages · cited by 2 Pith papers

  1. [1]

    A.; Parrinello, M

    Bonomi, M.; Branduardi, D.; Bussi, G.; Camilloni, C.; Provasi, D.; Raiteri, P.; Donadio, D.; Marinelli, F.; Pietrucci, F.; Broglia, R. A.; Parrinello, M. PLUMED: A portable plugin for free-energy calculations with molecular dynamics. Comput. Phys. Commun. 2009, 180, 1961--1972

    work page 2009

  2. [2]

    A.; Bonomi, M.; Branduardi, D.; Camilloni, C.; Bussi, G

    Tribello, G. A.; Bonomi, M.; Branduardi, D.; Camilloni, C.; Bussi, G. PLUMED 2: New feathers for an old bird. Comput. Phys. Commun. 2014, 185, 604--613

    work page 2014

  3. [3]

    COVID-19 and the academy: It is time for going digital

    Schwarz, M.; Scherrer, A.; Hohmann, C.; Heiberg, J.; Brugger, A.; Nuñez-Jimenez, A. COVID-19 and the academy: It is time for going digital. Energy Res. Soc. Sci. 2020, 68, 101684

    work page 2020

  4. [4]

    Bussi, G.; Branduardi, D. Rev. Comput. Chem., Volume 28; John Wiley and Sons, Ltd, 2015; Chapter 1, pp 1--49

    work page 2015

  5. [5]

    In Molecular Modeling of Proteins; Kukol, A., Ed.; Springer New York: New York, NY, 2015; pp 151--171

    Barducci, A.; Pfaendtner, J.; Bonomi, M. In Molecular Modeling of Proteins; Kukol, A., Ed.; Springer New York: New York, NY, 2015; pp 151--171

    work page 2015

  6. [6]

    In Biomolecular Simulations: Methods and Protocols; Bonomi, M., Camilloni, C., Eds.; Springer New York: New York, NY, 2019; pp 313--340

    L \"o hr, T.; Camilloni, C.; Bonomi, M.; Vendruscolo, M. In Biomolecular Simulations: Methods and Protocols; Bonomi, M., Camilloni, C., Eds.; Springer New York: New York, NY, 2019; pp 313--340

    work page 2019

  7. [7]

    Bussi, G.; Tribello, G. A. In Biomolecular Simulations: Methods and Protocols; Bonomi, M., Camilloni, C., Eds.; Springer New York: New York, NY, 2019; pp 529--578

    work page 2019

  8. [8]

    A.; Gasparotto, P

    Tribello, G. A.; Gasparotto, P. Using Dimensionality Reduction to Analyze Protein Trajectories. Front. Mol. Biosci. 2019, 6, 46

    work page 2019

Show all 49 references
  1. [9]

    A.; Gasparotto, P

    Tribello, G. A.; Gasparotto, P. Biomolecular Simulations: Methods and Protocols; Springer New York, 2019; Chapter Using data-reduction to analyze biomolecular trajectories

    2019

  2. [10]

    A.; Giberti, F.; Sosso, G

    Tribello, G. A.; Giberti, F.; Sosso, G. C.; Salvalaglio, M.; Parrinello, M. Analyzing and Driving Cluster Formation in Atomistic Simulations. J. Chem. Theory Comput. 2017, 13, 1317--1327

    2017

  3. [11]

    The PLUMED consortium, Promoting transparency and reproducibility in enhanced molecular simulations. Nat. Methods 2019, 16, 670--673

    2019

  4. [12]

    Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling

    Torrie, G.; Valleau, J. Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling. J. Comput. Phys. 1977, 23, 187--199

    1977

  5. [13]

    Escaping free-energy minima

    Laio, A.; Parrinello, M. Escaping free-energy minima. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 12562--12566

    2002

  6. [14]

    Replica-exchange molecular dynamics method for protein folding

    Sugita, Y.; Okamoto, Y. Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 1999, 314, 141--151

    1999

  7. [15]

    Analysis of the Results of Metadynamics Simulations by metadynminer and metadynminer3d

    Trapl, D.; Spiwok, V. Analysis of the Results of Metadynamics Simulations by metadynminer and metadynminer3d. R J. 2022, 14, 46--58

    2022

  8. [16]

    A unified framework for machine learning collective variables for enhanced sampling simulations: mlcolvar

    Bonati, L.; Trizio, E.; Rizzi, A.; Parrinello, M. A unified framework for machine learning collective variables for enhanced sampling simulations: mlcolvar . J. Chem. Phys. 2023, 159, 014801

    2023

  9. [17]

    M.; Invernizzi, M.; Bonati, L

    Trizio, E.; Rizzi, A.; Piaggi, P. M.; Invernizzi, M.; Bonati, L. Advanced simulations with PLUMED: OPES and Machine Learning Collective Variables. 2024; https://arxiv.org/abs/2410.18019

    2024 arXiv

  10. [18]

    Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations

    Ballabio, F.; Paissoni, C.; Bollati, M.; de Rosa, M.; Capelli, R.; Camilloni, C. Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations. J. Chem. Theory Comput. 2023, 19, 8401--8413

    2023

  11. [19]

    L.; Parrinello, M

    Branduardi, D.; Gervasio, F. L.; Parrinello, M. From A to B in free energy space . J. Chem. Phys. 2007, 126, 054103

    2007

  12. [20]

    Ligand binding free-energy calculations with funnel metadynamics

    Raniolo, S.; Limongelli, V. Ligand binding free-energy calculations with funnel metadynamics. Nat. Protoc. 2020, 15, 2837–2866

    2020

  13. [21]

    Exploration vs Convergence Speed in Adaptive-Bias Enhanced Sampling

    Invernizzi, M.; Parrinello, M. Exploration vs Convergence Speed in Adaptive-Bias Enhanced Sampling. Journal of Chemical Theory and Computation 2022, 18, 3988--3996, PMID: 35617155

    2022

  14. [22]

    D.; Voth, G

    White, A. D.; Voth, G. A. Efficient and Minimal Method to Bias Molecular Simulations with Experimental Data. J. Chem. Theory Comput. 2014, 10, 3023--3030

    2014

  15. [23]

    Accelerating All-Atom Simulations and Gaining Mechanistic Understanding of Biophysical Systems through State Predictive Information Bottleneck

    Mehdi, S.; Wang, D.; Pant, S.; Tiwary, P. Accelerating All-Atom Simulations and Gaining Mechanistic Understanding of Biophysical Systems through State Predictive Information Bottleneck. J. Chem. Theory Comput. 2022, 18, 3231--3238

    2022

  16. [24]

    Molecular dynamics simulations of solutions at constant chemical potential

    Perego, C.; Salvalaglio, M.; Parrinello, M. Molecular dynamics simulations of solutions at constant chemical potential . J. Chem. Phys. 2015, 142, 144113

    2015

  17. [25]

    Path Finding on High-Dimensional Free Energy Landscapes

    D\' az Leines, G.; Ensing, B. Path Finding on High-Dimensional Free Energy Landscapes. Phys. Rev. Lett. 2012, 109, 020601

    2012

  18. [26]

    Hamiltonian replica exchange in GROMACS: a flexible implementation

    Bussi, G. Hamiltonian replica exchange in GROMACS: a flexible implementation. Mol. Phys. 2014, 112, 379--384

    2014

  19. [27]

    Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials

    Pampel, B.; Valsson, O. Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials. Journal of Chemical Theory and Computation 2022, 18, 4127--4141, PMID: 35762642

    2022

  20. [28]

    M.; Parrinello, M

    Piaggi, P. M.; Parrinello, M. Calculation of phase diagrams in the multithermal-multibaric ensemble . J. Chem. Phys. 2019, 150, 244119

    2019

  21. [29]

    A Transfer Free Energy Based Implicit Solvent Model for Protein Simulations in Solvent Mixtures: Urea-Induced Denaturation as a Case Study

    Arsiccio, A.; Ganguly, P.; Shea, J.-E. A Transfer Free Energy Based Implicit Solvent Model for Protein Simulations in Solvent Mixtures: Urea-Induced Denaturation as a Case Study. J. Phys. Chem. B 2022, 126, 4472--4482

    2022

  22. [30]

    J.; Singh, Y.; Vanden-Eijnden, E.; Hocky, G

    Hartmann, M. J.; Singh, Y.; Vanden-Eijnden, E.; Hocky, G. M. Infinite switch simulated tempering in force (FISST) . J. Chem. Phys. 2020, 152, 244120

    2020

  23. [31]

    E.; Thomasen, F

    Hoff, S. E.; Thomasen, F. E.; Lindorff-Larsen, K.; Bonomi, M. Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference. PLOS Comput. Biol. 2024, 20, 1--26

    2024

  24. [32]

    Multi-replica biased sampling for photoswitchable -conjugated polymers

    Fortino, M.; Cozza, C.; Bonomi, M.; Pietropaolo, A. Multi-replica biased sampling for photoswitchable -conjugated polymers . J. Chem. Phys. 2021, 154, 174108

    2021

  25. [33]

    Exhaustive Search of Ligand Binding Pathways via Volume-Based Metadynamics

    Capelli, R.; Carloni, P.; Parrinello, M. Exhaustive Search of Ligand Binding Pathways via Volume-Based Metadynamics. J. Phys. Chem. Lett. 2019, 10, 3495--3499

    2019

  26. [34]

    Litman, Y. et al. i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations . J. Chem. Phys. 2024, 161, 062504

    2024

  27. [35]

    Silvestri, A.; Raiteri, P.; Gale, J. D. Obtaining Consistent Free Energies for Ion Binding at Surfaces from Solution: Pathways versus Alchemy for Determining Kink Site Stability. J. Chem. Theory Comput. 2022, 18, 5901--5919

    2022

  28. [36]

    F.; Rotskoff, G.; Parrinello, M.; Voth, G

    Dama, J. F.; Rotskoff, G.; Parrinello, M.; Voth, G. A. Transition-Tempered Metadynamics: Robust, Convergent Metadynamics via On-the-Fly Transition Barrier Estimation. J. Chem. Theory Comput. 2014, 10, 3626--3633

    2014

  29. [37]

    Finding multiple reaction pathways of ligand unbinding

    Rydzewski, J.; Valsson, O. Finding multiple reaction pathways of ligand unbinding . J. Chem. Phys. 2019, 150, 221101

    2019

  30. [38]

    Recent Advances and Emerging Challenges in the Molecular Modeling of Mechanobiological Processes

    Stirnemann, G. Recent Advances and Emerging Challenges in the Molecular Modeling of Mechanobiological Processes. J. Phys. Chem. B 2022, 126, 1365--1374

    2022

  31. [39]

    E.; Cavalli, A

    Bernetti, M.; Masetti, M.; Recanatini, M.; Amaro, R. E.; Cavalli, A. An Integrated Markov State Model and Path Metadynamics Approach To Characterize Drug Binding Processes. J. Chem. Theory Comput. 2019, 15, 5689--5702

    2019

  32. [40]

    Herringer, N. S. M.; Dasetty, S.; Gandhi, D.; Lee, J.; Ferguson, A. L. Permutationally Invariant Networks for Enhanced Sampling (PINES): Discovery of Multimolecular and Solvent-Inclusive Collective Variables. J. Chem. Theory Comput. 2024, 20, 178--198

    2024

  33. [41]

    F.; Zhang, S.; Vendruscolo, M

    Brotzakis, Z. F.; Zhang, S.; Vendruscolo, M. AlphaFold Prediction of Structural Ensembles of Disordered Proteins. bioRxiv 2023,

    2023

  34. [42]

    PYCV: a PLUMED 2 Module Enabling the Rapid Prototyping of Collective Variables in Python

    Giorgino, T. PYCV: a PLUMED 2 Module Enabling the Rapid Prototyping of Collective Variables in Python. J. Open Source Softw. 2019, 4, 1773

    2019

  35. [43]

    Febrer Martinez, P.; Rizzi, V.; Aureli, S.; Gervasio, F. L. Host-Guest binding free energies \`a la carte: an automated OneOPES protocol. J. Chem. Theory Comput. 2024,

    2024

  36. [44]

    M.; Pietrucci, F

    Pipolo, S.; Salanne, M.; Ferlat, G.; Klotz, S.; Saitta, A. M.; Pietrucci, F. Navigating at Will on the Water Phase Diagram. Phys. Rev. Lett. 2017, 119, 245701

    2017

  37. [45]

    Ab initio metadynamics determination of temperature-dependent free-energy landscape in ultrasmall silver clusters

    Sucerquia, D.; Parra, C.; Cossio, P.; Lopez-Acevedo, O. Ab initio metadynamics determination of temperature-dependent free-energy landscape in ultrasmall silver clusters . J. Chem. Phys. 2022, 156, 154301

    2022

  38. [46]

    F.; Bussi, G

    Silva, T. F.; Bussi, G. Characterizing RNA oligomers using Stochastic Titration Constant-pH Metadynamics simulations. 2024; https://arxiv.org/abs/2410.16064

    2024 arXiv

  39. [47]

    A Bias-Exchange Approach to Protein Folding

    Piana, S.; Laio, A. A Bias-Exchange Approach to Protein Folding. J. Phys. Chem. B 2007, 111, 4553--4559

    2007

  40. [48]

    V.; Garey, M

    Aho, A. V.; Garey, M. R.; Ullman, J. D. The Transitive Reduction of a Directed Graph. SIAM J. Comput. 1972, 1, 131--137

    1972

  41. [49]

    Carlo Bo

    Amaro, R. et al. The need to implement FAIR principles in biomolecular simulations. 2024; https://arxiv.org/abs/2407.16584 mcitethebibliography main.tex0000664000000000000000000020625114722310217011231 0ustar rootroot [journal=jacsat,manuscript=article] achemso [version=3] mhc...

    2024 arXiv

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Reviewed August 12, 2026 · model on record in the stance chip above.