ArticlePLoS computational biology2016
Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Molecular simulations reveal intricate coupling between agonist-bound β-adrenergic receptors and G protein.iScience · 2025Article
- Weighted ensemble: Recent mathematical developments.The Journal of chemical physics · 2023Article
- A Suite of Tutorials for the WESTPA 2.0 Rare-Events Sampling Software [Article v2.0].Living journal of computational molecular science · 2023Article
- Simulation of receptor triggering by kinetic segregation shows role of oligomers and close contacts.Biophysical journal · 2022Article
- WESTPA 2.0: High-Performance Upgrades for Weighted Ensemble Simulations and Analysis of Longer-Timescale Applications.Journal of chemical theory and computation · 2022Article
- A gentle introduction to the non-equilibrium physics of trajectories: Theory, algorithms, and biomolecular applications.American journal of physics · 2021Article
- A first-passage approach to diffusion-influenced reversible binding and its insights into nanoscale signaling at the presynapse.Scientific reports · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- Wepy: A Flexible Software Framework for Simulating Rare Events with Weighted Ensemble Resampling.ACS omega · 2020Article
- Accelerated Estimation of Long-Timescale Kinetics from Weighted Ensemble Simulation via Non-Markovian "Microbin" Analysis.Journal of chemical theory and computation · 2020Article
- Automatic error control during forward flux sampling of rare events in master equation models.The Journal of chemical physics · 2020Article
- Potential based, spatial simulation of dynamically nested particles.BMC bioinformatics · 2019Article
- Computational Estimation of Microsecond to Second Atomistic Folding Times.Journal of the American Chemical Society · 2019Article
- A Suite of Tutorials for the WESTPA Rare-Events Sampling Software [Article v1.0].Living journal of computational molecular science · 2019Article
- MCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Rare-event sampling of epigenetic landscapes and phenotype transitions.PLoS computational biology · 2018Article
- Multifidelity Analysis for Predicting Rare Events in Stochastic Computational Models of Complex Biological Systems.Biomedical engineering and computational biology · 2018Article
- Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.Annual review of biophysics · 2017Review
- Path-sampling strategies for simulating rare events in biomolecular systems.Current opinion in structural biology · 2017Review
- Efficient Atomistic Simulation of Pathways and Calculation of Rate Constants for a Protein-Peptide Binding Process: Application to the MDM2 Protein and an Intrinsically Disordered p53 Peptide.The journal of physical chemistry letters · 2016Article
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Authors and funding
7 authors.
Funding
Abstract
The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation--by orders of magnitude for some observables.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.