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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of proteins binding coding and non-coding human RNAs using protein microarrays
|
|---|---|
| Published in |
BMC Genomics, November 2012
|
| DOI | 10.1186/1471-2164-13-633 |
| Pubmed ID | |
| Authors |
Zurab Siprashvili, Dan E Webster, Markus Kretz, Danielle Johnston, John L Rinn, Howard Y Chang, Paul A Khavari |
| Abstract |
The regulation and function of mammalian RNAs has been increasingly appreciated to operate via RNA-protein interactions. With the recent discovery of thousands of novel human RNA molecules by high-throughput RNA sequencing, efficient methods to uncover RNA-protein interactions are urgently required. Existing methods to study proteins associated with a given RNA are laborious and require substantial amounts of cell-derived starting material. To overcome these limitations, we have developed a rapid and large-scale approach to characterize binding of in vitro transcribed labeled RNA to ~9,400 human recombinant proteins spotted on protein microarrays. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| Germany | 1 | 1% |
| Malaysia | 1 | 1% |
| South Africa | 1 | 1% |
| France | 1 | 1% |
| Japan | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 89 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 31% |
| Researcher | 23 | 24% |
| Student > Master | 11 | 11% |
| Student > Bachelor | 6 | 6% |
| Student > Postgraduate | 5 | 5% |
| Other | 15 | 15% |
| Unknown | 7 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 47 | 48% |
| Biochemistry, Genetics and Molecular Biology | 24 | 25% |
| Engineering | 6 | 6% |
| Medicine and Dentistry | 4 | 4% |
| Computer Science | 3 | 3% |
| Other | 4 | 4% |
| Unknown | 9 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 March 2018.
All research outputs
#6,113,671
of 22,685,926 outputs
Outputs from BMC Genomics
#2,610
of 10,616 outputs
Outputs of similar age
#40,013
of 159,110 outputs
Outputs of similar age from BMC Genomics
#38
of 146 outputs
Altmetric has tracked 22,685,926 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 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 74% 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 159,110 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 74% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.