Evidence map›Paper›PMID 22286385›Full record

ArticleNature methods2012

Computational modeling of cellular signaling processes embedded into dynamic spatial contexts.

Bastian R Angermann, Frederick Klauschen, Alex D Garcia, Thorsten Prustel, Fengkai Zhang, Ronald N Germain, Martin Meier-Schellersheim

Abstract read
In one paragraph

Article in Nature methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
5.5field-weighted citation impact, top 3% of its field
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

45 citing papers in PubMed, 96 citations in OpenAlex.

  1. Article
  2. drexml: A command line tool and Python package for drug repurposing.Computational and structural biotechnology journal · 2024
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Programmatic modeling for biological systems.Current opinion in systems biology · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. MCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework.Methods in molecular biology (Clifton, N.J.) · 2019
    Article
  13. Article
  14. Review
  15. Article
  16. Review
  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

7 authors at 3 institutions in 2 countries.

Bastian R AngermannLaboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Frederick Klauschen
Alex D Garcia
Thorsten Prustel
Fengkai Zhang
Ronald N Germain
Martin Meier-Schellersheim
National Institutes of Health · USNational Institute of Allergy and Infectious Diseases · USCharité - Universitätsmedizin Berlin · DE

Funding

Computational Biology in Systems Immunology and Infectious Disease ModelingZIAAI001076 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI MEIER-SCHELLERSHEIM, MARTIN · 2009 to 2025
$25.4M
Immunology Team Contributions to the PSIIMZIAAI000974 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI GERMAIN, RONALD N · 2009 to 2025
$6.9M
Computational Biology in Systems Immunology and Infectious Disease Modeling Z01AI001076 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI MEIER-SCHELLERSHEIM, MARTIN · 2008 to 2008
$2.7M
Intramural NIH HHS Z01 AI001076Intramural NIH HHS ZIA AI001076
6 · The paper itself

Abstract

Cellular signaling processes depend on spatiotemporal distributions of molecular components. Multicolor, high-resolution microscopy permits detailed assessment of such distributions, providing input for fine-grained computational models that explore mechanisms governing dynamic assembly of multimolecular complexes and their role in shaping cellular behavior. However, it is challenging to incorporate into such models both complex molecular reaction cascades and the spatial localization of signaling components in dynamic cellular morphologies. Here we introduce an approach to address these challenges by automatically generating computational representations of complex reaction networks based on simple bimolecular interaction rules embedded into detailed, adaptive models of cellular morphology. Using examples of receptor-mediated cellular adhesion and signal-induced localized mitogen-activated protein kinase (MAPK) activation in yeast, we illustrate the capacity of this simulation technique to provide insights into cell biological processes. The modeling algorithms, implemented in a new version of the Simmune toolset, are accessible through intuitive graphical interfaces and programming libraries.

Indexed as

Cell SizeModels, AnatomicModels, BiologicalAnimalsComputer SimulationHumansSignal Transduction

Identifiers

PMID22286385
PMCPMC3448286
OpenAlexW2014449669

What OpenQuestion holds

Textmetadata
LicenceTDM
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.