Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

Rory M. Donovan, Jose Juan Tapia, Devin P. Sullivan, James R. Faeder, Robert F. Murphy, Markus Dittrich, Daniel Zuckerman

Research output: Contribution to journalArticle

8 Citations (Scopus)

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.

Original languageEnglish (US)
Article numbere1004611
JournalPLoS Computational Biology
Volume12
Issue number2
DOIs
StatePublished - Feb 1 2016
Externally publishedYes

Fingerprint

Systems Biology
Rare Events
Stochastic systems
Stochastic Systems
trajectories
Ensemble
trajectory
Trajectories
Trajectory
Sampling
Biological Sciences
sampling
Cell membranes
cell aggregates
pruning
Organelles
simulation
organelles
plasma membrane
Cell Membrane

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Cite this

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories. / Donovan, Rory M.; Tapia, Jose Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel.

In: PLoS Computational Biology, Vol. 12, No. 2, e1004611, 01.02.2016.

Research output: Contribution to journalArticle

Donovan, Rory M. ; Tapia, Jose Juan ; Sullivan, Devin P. ; Faeder, James R. ; Murphy, Robert F. ; Dittrich, Markus ; Zuckerman, Daniel. / Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories. In: PLoS Computational Biology. 2016 ; Vol. 12, No. 2.
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