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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
RAP-MS: A Method to Identify Proteins that Interact Directly with a Specific RNA Molecule in Cells
|
|---|---|
| Chapter number | 31 |
| Book title |
RNA Detection
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7213-5_31 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7212-8, 978-1-4939-7213-5
|
| Authors |
Colleen A. McHugh, Mitchell Guttman, McHugh, Colleen A., Guttman, Mitchell |
| Abstract |
RNA molecules interact with proteins to perform a variety of functions in living cells. The binding partners of many RNAs, in particular the newly discovered class of long noncoding RNAs (lncRNAs), remain largely unknown. RNA antisense purification coupled with mass spectrometry (RAP-MS) is a method that enables the identification of direct and specific protein interaction partners of a specific RNA molecule. Because RAP-MS uses direct RNA-protein cross-linking methods coupled along with highly denaturing purification conditions, RAP-MS provides a short list of high confidence protein interactors. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 118 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 34 | 29% |
| Student > Master | 13 | 11% |
| Researcher | 12 | 10% |
| Student > Bachelor | 8 | 7% |
| Student > Doctoral Student | 5 | 4% |
| Other | 17 | 14% |
| Unknown | 29 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 49 | 42% |
| Agricultural and Biological Sciences | 15 | 13% |
| Chemistry | 6 | 5% |
| Immunology and Microbiology | 5 | 4% |
| Unspecified | 4 | 3% |
| Other | 7 | 6% |
| Unknown | 32 | 27% |
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 23 June 2022.
All research outputs
#6,346,202
of 22,721,584 outputs
Outputs from Methods in molecular biology
#1,909
of 13,084 outputs
Outputs of similar age
#130,204
of 440,676 outputs
Outputs of similar age from Methods in molecular biology
#175
of 1,498 outputs
Altmetric has tracked 22,721,584 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 13,084 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 85% 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 440,676 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 70% of its contemporaries.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.