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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Use of RNAlater in fluorescence-activated cell sorting (FACS) reduces the fluorescence from GFP but not from DsRed
|
|---|---|
| Published in |
BMC Research Notes, December 2010
|
| DOI | 10.1186/1756-0500-3-328 |
| Pubmed ID | |
| Authors |
Ismail Zaitoun, Christopher S Erickson, Kathy Schell, Miles L Epstein |
| Abstract |
Flow cytometry utilizes signals from fluorescent markers to separate targeted cell populations for gene expression studies. However, the stress of the FACS process could change normal gene expression profiles. RNAlater could be used to stop such changes in original gene expression profiles through its ability to denature RNase and other proteins. The normal conformational structure of fluorescent proteins must be maintained in order to fluoresce. Whether or not RNAlater would affect signals from different types of intrinsic fluorescent proteins is crucial to its use in flow cytometry; this question has not been investigated in detail. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| Netherlands | 1 | 1% |
| United Kingdom | 1 | 1% |
| Australia | 1 | 1% |
| Japan | 1 | 1% |
| Denmark | 1 | 1% |
| Unknown | 75 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 31% |
| Student > Ph. D. Student | 23 | 28% |
| Other | 6 | 7% |
| Student > Master | 6 | 7% |
| Student > Postgraduate | 4 | 5% |
| Other | 10 | 12% |
| Unknown | 8 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 40% |
| Biochemistry, Genetics and Molecular Biology | 14 | 17% |
| Medicine and Dentistry | 9 | 11% |
| Neuroscience | 5 | 6% |
| Immunology and Microbiology | 5 | 6% |
| Other | 6 | 7% |
| Unknown | 11 | 13% |
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 17 January 2012.
All research outputs
#15,241,259
of 22,661,413 outputs
Outputs from BMC Research Notes
#2,308
of 4,248 outputs
Outputs of similar age
#140,184
of 180,088 outputs
Outputs of similar age from BMC Research Notes
#24
of 32 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,248 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 33rd percentile – i.e., 33% 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 180,088 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.