Evidence map›Paper›PMID 21326200›Full record

ReviewNature reviews. Molecular cell biology2011

Moving into the cell: single-molecule studies of molecular motors in complex environments.

Claudia Veigel, Christoph F Schmidt

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Molecular cell biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing 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

66 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Appetizer on soft matter physics concepts in mechanobiology.Development, growth & differentiation · 2023
    Review
  8. Article
  9. Watching biomolecules stride in real time.Science (New York, N.Y.) · 2023
    Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Detection of Steps and Rotation in the Gliding Motility of Mycoplasma mobile.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article

6 more citing papers are in PubMed but not listed here.

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.

Claudia VeigelDepartment of Cellular Physiology, Institute of Physiology, Ludwig-Maximilians-Universität München, Schillerstrasse 44, 80336 München, Germany. claudia.veigel@med.uni-muenchen.de
Christoph F Schmidt

Funding

Medical Research Council
6 · The paper itself

Abstract

Much has been learned in the past decades about molecular force generation. Single-molecule techniques, such as atomic force microscopy, single-molecule fluorescence microscopy and optical tweezers, have been key in resolving the mechanisms behind the power strokes, 'processive' steps and forces of cytoskeletal motors. However, it remains unclear how single force generators are integrated into composite mechanical machines in cells to generate complex functions such as mitosis, locomotion, intracellular transport or mechanical sensory transduction. Using dynamic single-molecule techniques to track, manipulate and probe cytoskeletal motor proteins will be crucial in providing new insights.

Indexed as

AnimalsCytoskeletal ProteinsFluorescent DyesHumansLightMicroscopy, Atomic ForceMicroscopy, FluorescenceModels, BiologicalMolecular Motor ProteinsOptical TweezersQuantum DotsScattering, RadiationSingle-Cell AnalysisCytoskeletal ProteinsFluorescent DyesMolecular Motor Proteins

Identifiers

PMID21326200

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.