Evidence map›Paper›PMID 20691138›Full record

ReviewQuarterly reviews of biophysics2010

Rate theories for biologists.

Huan-Xiang Zhou

Abstract readReview
In one paragraph

Review in Quarterly reviews of biophysics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Allocation of resources among multiple daughter cells.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. A general theory for temperature dependence in biology.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  7. Interplay of Affinity and Surface Tethering in Protein Recognition.The journal of physical chemistry letters · 2022
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Assessing the Role of Calmodulin's Linker Flexibility in Target Binding.International journal of molecular sciences · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. 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

1 author.

Huan-Xiang ZhouDepartment of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, FL 32306, USA. hzhou4@fsu.edu

Funding

THEORY OF PROTEIN/PROTEIN ASSOCIATIONR01GM058187 · NIGMS · FLORIDA STATE UNIVERSITY · PI ZHOU, HUAN-XIANG · 1998 to 2016
$3.7M
NIGMS NIH HHS GM58187NIGMS NIH HHS R01 GM058187
6 · The paper itself

Abstract

Some of the rate theories that are most useful for modeling biological processes are reviewed. By delving into some of the details and subtleties in the development of the theories, the review will hopefully help the reader gain a more than superficial perspective. Examples are presented to illustrate how rate theories can be used to generate insight at the microscopic level into biomolecular behaviors. An attempt is made to clear up a number of misconceptions in the literature regarding popular rate theories, including the appearance of Planck's constant in the transition-state theory and the Smoluchowski result as an upper limit for protein-protein and protein-DNA association rate constants. Future work in combining the implementation of rate theories through computer simulations with experimental probes of rate processes, and in modeling effects of intracellular environments so that theories can be used for generating rate constants for systems biology studies is particularly exciting.

Indexed as

BiologyHumansKineticsModels, BiologicalModels, ChemicalProtein ConformationProteinsProteins

Identifiers

PMID20691138
PMCPMC3540998

What OpenQuestion holds

Textmetadata
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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.