Evidence map›Paper›PMID 34421402›Full record

ArticleMultiscale modeling & simulation : a SIAM interdisciplinary journal2020

OPTIMIZING WEIGHTED ENSEMBLE SAMPLING OF STEADY STATES.

David Aristoff, Daniel M Zuckerman

Abstract read
In one paragraph

Article in Multiscale modeling & simulation : a SIAM interdisciplinary journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Weighted ensemble: Recent mathematical developments.The Journal of chemical physics · 2023
    Article
  3. A Suite of Tutorials for the WESTPA 2.0 Rare-Events Sampling Software [Article v2.0].Living journal of computational molecular science · 2023
    Article
  4. Article
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  11. Article
  12. Weighted Ensemble Simulation: Advances in methods, software, and applications.Wiley interdisciplinary reviews. Computational molecular science
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

David AristoffColorado State University, Fort Collins, CO 80523.
Daniel M ZuckermanOregon Health & Science University, Portland, OR 97239.

Funding

WESTPA: A high-performance framework for simulating at the frontiers of biologyR01GM115805 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LILLIAN T CHONG · 2015 to 2026
$4.0M
NIGMS NIH HHS R01 GM115805
6 · The paper itself

Abstract

We propose parameter optimization techniques for weighted ensemble sampling of Markov chains in the steady-state regime. Weighted ensemble consists of replicas of a Markov chain, each carrying a weight, that are periodically resampled according to their weights inside of each of a number of bins that partition state space. We derive, from first principles, strategies for optimizing the choices of weighted ensemble parameters, in particular the choice of bins and the number of replicas to maintain in each bin. In a simple numerical example, we compare our new strategies with more traditional ones and with direct Monte Carlo.

Indexed as

65C0565C2065C4065Y0582C80coarse grainingMarkov chainsmolecular dynamicsreaction networksresamplingsequential Monte Carlosteady stateweighted ensemble

Identifiers

PMID34421402
PMCPMC8378190

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.