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Thermodynamics of Biological Processes

Overview of attention for chapter in “Biothermodynamics, Part D”
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
6 X users
patent
1 patent
facebook
1 Facebook page
reddit
4 Redditors

Readers on

mendeley
280 Mendeley
citeulike
2 CiteULike
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Article details
Chapter title
Thermodynamics of Biological Processes
Book title
Biothermodynamics, Part D
Published in
Methods in enzymology, May 2013
DOI 10.1016/b978-0-12-381268-1.00014-8
Pubmed ID
Book ISBNs
978-0-12-386003-3
Authors

Hernan G. Garcia, Jane Kondev, Nigel Orme, Julie A. Theriot, Rob Phillips

Abstract

There is a long and rich tradition of using ideas from both equilibrium thermodynamics and its microscopic partner theory of equilibrium statistical mechanics. In this chapter, we provide some background on the origins of the seemingly unreasonable effectiveness of ideas from both thermodynamics and statistical mechanics in biology. After making a description of these foundational issues, we turn to a series of case studies primarily focused on binding that are intended to illustrate the broad biological reach of equilibrium thinking in biology. These case studies include ligand-gated ion channels, thermodynamic models of transcription, and recent applications to the problem of bacterial chemotaxis. As part of the description of these case studies, we explore a number of different uses of the famed Monod-Wyman-Changeux (MWC) model as a generic tool for providing a mathematical characterization of two-state systems. These case studies should provide a template for tailoring equilibrium ideas to other problems of biological interest.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 280 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 6 2%
United Kingdom 2 <1%
Switzerland 2 <1%
South Africa 1 <1%
Romania 1 <1%
Norway 1 <1%
Japan 1 <1%
India 1 <1%
France 1 <1%
Other 0 0%
Unknown 264 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 67 24%
Researcher 63 23%
Student > Master 27 10%
Student > Bachelor 21 8%
Professor > Associate Professor 20 7%
Other 41 15%
Unknown 41 15%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 87 31%
Biochemistry, Genetics and Molecular Biology 38 14%
Physics and Astronomy 29 10%
Chemistry 21 8%
Engineering 21 8%
Other 30 11%
Unknown 54 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 February 2025.
All research outputs
#4,715,935
of 32,718,554 outputs
Outputs from Methods in enzymology
#602
of 5,878 outputs
Outputs of similar age
#34,624
of 228,845 outputs
Outputs of similar age from Methods in enzymology
#1
of 5 outputs
Altmetric has tracked 32,718,554 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,878 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 228,845 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them