Evidence map›Paper›PMID 23231214›Full record

ArticleThe Journal of chemical physics2012

A hierarchical exact accelerated stochastic simulation algorithm.

David Orendorff, Eric Mjolsness

Abstract read
In one paragraph

Article in The Journal of chemical physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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 OrendorffDepartment of Computer Science, University of California, Irvine, California 92697, USA.
Eric Mjolsness

Funding

Uncover Strategies Used By Biological SystemsP50GM076516 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LANDER, ARTHUR D · 2007 to 2016
$25.1M
Stochastic dynamics for multiscale biologyR01GM086883 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI MJOLSNESS, ERIC D · 2008 to 2011
$1.2M
NIGMS NIH HHS P50 GM076516NIGMS NIH HHS P50-GM76516NIGMS NIH HHS R01 GM086883NIGMS NIH HHS R01-GM086883
6 · The paper itself

Abstract

A new algorithm, "HiER-leap" (hierarchical exact reaction-leaping), is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or divide-and-conquer organization of reaction channels into tightly coupled "blocks" and is thereby able to speed up systems with many reaction channels. Like ER-leap, HiER-leap is based on the use of upper and lower bounds on the reaction propensities to define a rejection sampling algorithm with inexpensive early rejection and acceptance steps. But in HiER-leap, large portions of intra-block sampling may be done in parallel. An accept/reject step is used to synchronize across blocks. This method scales well when many reaction channels are present and has desirable asymptotic properties. The algorithm is exact, parallelizable and achieves a significant speedup over the stochastic simulation algorithm and ER-leap on certain problems. This algorithm offers a potentially important step towards efficient in silico modeling of entire organisms.

Indexed as

AlgorithmsModels, ChemicalKineticsMarkov ChainsReproducibility of ResultsStochastic Processes

Identifiers

PMID23231214
PMCPMC3531277

What OpenQuestion holds

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Registered trials

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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.