Evidence map›Paper›PMID 27761104›Full record

ArticleMultiscale modeling & simulation : a SIAM interdisciplinary journal2016

ACCURATE CHEMICAL MASTER EQUATION SOLUTION USING MULTI-FINITE BUFFERS.

Youfang Cao, Anna Terebus, Jie Liang

Abstract read
In one paragraph

Article in Multiscale modeling & simulation : a SIAM interdisciplinary journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
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  4. Distilling dynamical knowledge from stochastic reaction networks.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Review
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  7. Inferring initial state of the ancestral network of cellular fate decision: a case study of phage lambda.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Sensitivities of Regulation Intensities in Feed-Forward Loops with Multistability.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2019
    Article
  14. Article
  15. Article
  16. Probabilistic control of HIV latency and transactivation by the Tat gene circuit.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  17. Article
  18. Article
  19. Article
  20. 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.

Youfang CaoDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
Anna TerebusDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
Jie LiangDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.

Funding

Computational assembly of beta-barrel membrane proteinsR01GM079804 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE · 2007 to 2016
$2.8M
NIGMS NIH HHS R01 GM079804
6 · The paper itself

Abstract

The discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multi-scale nature of many networks where reaction rates have large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the Accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multi-finite buffers for reducing the state space by

Indexed as

chemical master equationfirst passage time distributionstate space truncationsteady state probability landscapestochastic biological networkstime-evolving probability landscapes

Identifiers

PMID27761104
PMCPMC5066912

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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.