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Attention Score in Context
Title |
Characterization of human plasma-derived exosomal RNAs by deep sequencing
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Published in |
BMC Genomics, May 2013
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DOI | 10.1186/1471-2164-14-319 |
Pubmed ID | |
Authors |
Xiaoyi Huang, Tiezheng Yuan, Michael Tschannen, Zhifu Sun, Howard Jacob, Meijun Du, Meihua Liang, Rachel L Dittmar, Yong Liu, Mingyu Liang, Manish Kohli, Stephen N Thibodeau, Lisa Boardman, Liang Wang |
Abstract |
Exosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, we performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all we evaluated 14 libraries (7 replicates). |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | 17% |
United Kingdom | 1 | 17% |
Belgium | 1 | 17% |
France | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 67% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 960 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | <1% |
Japan | 3 | <1% |
Belgium | 3 | <1% |
Brazil | 3 | <1% |
Netherlands | 2 | <1% |
Denmark | 2 | <1% |
Germany | 2 | <1% |
France | 1 | <1% |
Sweden | 1 | <1% |
Other | 6 | <1% |
Unknown | 930 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 225 | 23% |
Researcher | 178 | 19% |
Student > Master | 94 | 10% |
Student > Bachelor | 75 | 8% |
Student > Doctoral Student | 49 | 5% |
Other | 134 | 14% |
Unknown | 205 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 258 | 27% |
Biochemistry, Genetics and Molecular Biology | 224 | 23% |
Medicine and Dentistry | 103 | 11% |
Neuroscience | 27 | 3% |
Engineering | 22 | 2% |
Other | 83 | 9% |
Unknown | 243 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 15 November 2023.
All research outputs
#2,159,476
of 24,814,419 outputs
Outputs from BMC Genomics
#556
of 11,075 outputs
Outputs of similar age
#17,593
of 197,715 outputs
Outputs of similar age from BMC Genomics
#6
of 117 outputs
Altmetric has tracked 24,814,419 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,075 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 94% 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 197,715 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 117 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.