Evidence map›Paper›PMID 16229621›Full record

ArticleThe Journal of chemical physics2005

Reactions on cell membranes: comparison of continuum theory and Brownian dynamics simulations.

Michael I Monine, Jason M Haugh

Open access · greenAbstract readComparative Study
In one paragraph

Article in The Journal of chemical physics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

9 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. A spatio-temporal model reveals self-limiting FcRoyal Society open science · 2018
    Article
  3. A model-based analysis of tissue targeting efficacy of nanoparticles.Journal of the Royal Society, Interface · 2018
    Article
  4. Article
  5. Review
  6. Dynamics of enzymatic digestion of elastic fibers and networks under tension.Proceedings of the National Academy of Sciences of the United States of America · 2011
    Article
  7. Article
  8. Article
  9. 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 at 1 institution in 1 country.

Michael I MonineDepartment of Chemical and Biomolecular Engineering, North Carolina State University, Box 7905, 911 Partners Way, Raleigh, North Carolina 27695-7905, USA.
Jason M Haugh
North Carolina State University · US

Funding

Molecular Crosstalk in Intracellular Signaling NetworksR01GM067739 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI HAUGH, JASON M. · 2003 to 2006
$704k
NIGMS NIH HHS R01 GM067739NIGMS NIH HHS R01-GM067739
6 · The paper itself

Abstract

Biochemical transduction of signals received by living cells typically involves molecular interactions and enzyme-mediated reactions at the cell membrane, a problem that is analogous to reacting species on a catalyst surface or interface. We have developed an efficient Brownian dynamics algorithm that is especially suited for such systems and have compared the simulation results with various continuum theories through prediction of effective enzymatic rate constant values. We specifically consider reaction versus diffusion limitation, the effect of increasing enzyme density, and the spontaneous membrane association/dissociation of enzyme molecules. In all cases, we find the theory and simulations to be in quantitative agreement. This algorithm may be readily adapted for the stochastic simulation of more complex cell signaling systems.

Indexed as

AlgorithmsBiophysicsCatalysisCell MembraneChemistry, PhysicalComputer SimulationDiffusionEnzymesModels, StatisticalModels, TheoreticalMolecular ConformationSignal TransductionStatic ElectricitySubstrate SpecificityEnzymes

Identifiers

PMID16229621
PMCPMC1752218
OpenAlexW2064844308

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.