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Unmixing of fluorescence spectra to resolve quantitative time-series measurements of gene expression in plate readers

Overview of attention for article published in BMC Biotechnology, February 2014
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Title
Unmixing of fluorescence spectra to resolve quantitative time-series measurements of gene expression in plate readers
Published in
BMC Biotechnology, February 2014
DOI 10.1186/1472-6750-14-11
Pubmed ID
Authors

Catherine A Lichten, Rachel White, Ivan BN Clark, Peter S Swain

Abstract

To connect gene expression with cellular physiology, we need to follow levels of proteins over time. Experiments typically use variants of Green Fluorescent Protein (GFP), and time-series measurements require specialist expertise if single cells are to be followed. Fluorescence plate readers, however, a standard in many laboratories, can in principle provide similar data, albeit at a mean, population level. Nevertheless, extracting the average fluorescence per cell is challenging because autofluorescence can be substantial.

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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
France 1 1%
Unknown 67 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 33%
Student > Master 9 13%
Researcher 7 10%
Student > Bachelor 5 7%
Student > Postgraduate 5 7%
Other 13 19%
Unknown 7 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 32%
Biochemistry, Genetics and Molecular Biology 20 29%
Engineering 3 4%
Chemistry 3 4%
Business, Management and Accounting 2 3%
Other 8 12%
Unknown 11 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 May 2014.
All research outputs
#9,906,227
of 12,373,386 outputs
Outputs from BMC Biotechnology
#556
of 695 outputs
Outputs of similar age
#154,495
of 227,612 outputs
Outputs of similar age from BMC Biotechnology
#41
of 61 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 695 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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 227,612 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.