Evidence map›Paper›PMID 25606671›Full record

ArticleBiophysical journal2015

Local perturbation analysis: a computational tool for biophysical reaction-diffusion models.

William R Holmes, May Anne Mata, Leah Edelstein-Keshet

Abstract read
In one paragraph

Article in Biophysical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Characterizing spontaneous CaBiophysical journal · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Mechanisms of Cell Polarization.Current opinion in systems biology · 2017
    Article
  18. Article
  19. 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.

William R HolmesDepartment of Mathematics, University of Melbourne, Parkville, Australia; Center for Mathematical and Computational Biology, Center for Complex Biological Systems, Department of Mathematics, University of California Irvine, Irvine, California. Electronic address: holmesw@unimelb.edu.au.
May Anne MataI. K. Barber School of Arts and Sciences, University of British Columbia Okanagan, Kelowna, British Columbia, Canada; Department of Math, Physics, and Computer Science, University of the Philippines Mindanao, Davao City, Philippines.
Leah Edelstein-KeshetDepartment of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.

Funding

Uncover Strategies Used By Biological SystemsP50GM076516 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LANDER, ARTHUR D · 2007 to 2016
$25.1M
NIGMS NIH HHS P50 GM076516NIGMS NIH HHS P50GM76516
6 · The paper itself

Abstract

Diffusion and interaction of molecular regulators in cells is often modeled using reaction-diffusion partial differential equations. Analysis of such models and exploration of their parameter space is challenging, particularly for systems of high dimensionality. Here, we present a relatively simple and straightforward analysis, the local perturbation analysis, that reveals how parameter variations affect model behavior. This computational tool, which greatly aids exploration of the behavior of a model, exploits a structural feature common to many cellular regulatory systems: regulators are typically either bound to a membrane or freely diffusing in the interior of the cell. Using well-documented, readily available bifurcation software, the local perturbation analysis tracks the approximate early evolution of an arbitrarily large perturbation of a homogeneous steady state. In doing so, it provides a bifurcation diagram that concisely describes various regimes of the model's behavior, reducing the need for exhaustive simulations to explore parameter space. We explain the method and provide detailed step-by-step guides to its use and application.

Indexed as

Models, BiologicalSoftwareDiffusionrho GTP-Binding Proteinsrho GTP-Binding Proteins

Identifiers

PMID25606671
PMCPMC4302203

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.