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A Bayesian method for inferring quantitative information from FRET data

Overview of attention for article published in BMC Biophysics, May 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

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1 tweeter
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1 patent

Citations

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4 Dimensions

Readers on

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39 Mendeley
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Title
A Bayesian method for inferring quantitative information from FRET data
Published in
BMC Biophysics, May 2011
DOI 10.1186/2046-1682-4-10
Pubmed ID
Authors

Catherine A Lichten, Peter S Swain

Abstract

Understanding biological networks requires identifying their elementary protein interactions and establishing the timing and strength of those interactions. Fluorescence microscopy and Förster resonance energy transfer (FRET) have the potential to reveal such information because they allow molecular interactions to be monitored in living cells, but it is unclear how best to analyze FRET data. Existing techniques differ in assumptions, manipulations of data and the quantities they derive. To address this variation, we have developed a versatile Bayesian analysis based on clear assumptions and systematic statistics.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 10 26%
Professor > Associate Professor 4 10%
Student > Master 4 10%
Student > Doctoral Student 3 8%
Other 6 15%
Unknown 2 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 38%
Physics and Astronomy 6 15%
Biochemistry, Genetics and Molecular Biology 5 13%
Chemistry 4 10%
Neuroscience 2 5%
Other 3 8%
Unknown 4 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 November 2015.
All research outputs
#3,369,125
of 12,440,051 outputs
Outputs from BMC Biophysics
#16
of 66 outputs
Outputs of similar age
#29,746
of 116,705 outputs
Outputs of similar age from BMC Biophysics
#2
of 4 outputs
Altmetric has tracked 12,440,051 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 66 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 75% 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 116,705 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.