Evidence map›Paper›PMID 26026435›Full record

ArticleThe Journal of chemical physics2015

Adaptive deployment of model reductions for tau-leaping simulation.

Sheng Wu, Jin Fu, Linda R Petzold

Abstract readComparative Study
In one paragraph

Article in The Journal of chemical physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Sheng WuDepartment of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, USA.
Jin FuDepartment of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, USA.
Linda R PetzoldDepartment of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, USA.

Funding

StochSS: A Next-Generation Toolkit for Simulation-Driven Biological DiscoveryR01EB014877 · NIBIB · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI PETZOLD, LINDA R. · 2012 to 2022
$3.9M
NIBIB NIH HHS R01 EB014877NIBIB NIH HHS R01EB014877
6 · The paper itself

Abstract

Multiple time scales in cellular chemical reaction systems often render the tau-leaping algorithm inefficient. Various model reductions have been proposed to accelerate tau-leaping simulations. However, these are often identified and deployed manually, requiring expert knowledge. This is time-consuming and prone to error. In previous work, we proposed a methodology for automatic identification and validation of model reduction opportunities for tau-leaping simulation. Here, we show how the model reductions can be automatically and adaptively deployed during the time course of a simulation. For multiscale systems, this can result in substantial speedups.

Indexed as

Computer SimulationModels, TheoreticalElectronsFormaldehydeSpectrum AnalysisFormaldehyde

Identifiers

PMID26026435
PMCPMC4449353

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.