MolSieve: A Progressive Visual Analytics System for Molecular Dynamics Simulations

Hnatyshyn, Rostyslav; Zhao, Jieqiong; Perez, Danny; Ahrens, James; Maciejewski, Ross

doi:10.1109/tvcg.2023.3326584

Cited by 1 publication

(2 citation statements)

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“…In 2020, a collaborative initiative resulted in the establishment of an MolSieve is a progressive visual analytics system for comparing multiple long-duration simulations. It is able to quickly identify and compare regions of interest within immense simulation ensembles thanks to its combination of control charts, data-reduction techniques and highly informative visual components (Hnatyshyn et al, 2024). We thank the authors for providing an image depicting a typical MolSieve session.…”

Section: Databases For Molecular Simulationsmentioning

confidence: 99%

“…Such comparative visualization can be adapted for an ensemble of molecular simulations. Another visual analytics system, MolSieve ( Hnatyshyn et al, 2024 ), enables the comparison of multiple long-duration simulations modeled by discrete Markov chains ( Figure 13 ). It reduces molecular dynamics simulations to their essential components (super-states and transition regions) to facilitate their analysis and comparison.…”

Section: Scaling Up To Simulation Ensembles and Data Sharingmentioning

confidence: 99%

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From complex data to clear insights: visualizing molecular dynamics trajectories

Belghit,

Spivak,

Dauchez

et al. 2024

Front. Bioinform.

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Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.

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Section: Databases For Molecular Simulationsmentioning

confidence: 99%

Section: Scaling Up To Simulation Ensembles and Data Sharingmentioning

confidence: 99%