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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
RNA Structure Determination
|
|---|---|
| Chapter number | 8 |
| Book title |
RNA Structure Determination
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-6433-8_8 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6431-4, 978-1-4939-6433-8
|
| Authors |
Uzilov, Andrew V, Underwood, Jason G, Andrew V. Uzilov, Jason G. Underwood |
| Abstract |
High-throughput sequencing of cDNA (RNA-Seq) can be used to generate nuclease accessibility data for many distinct transcripts in the same mixture simultaneously. Such assays accelerate RNA structure analysis and provide researchers with new technologies to tackle biological questions on a transcriptome-wide scale. FragSeq is an experimental assay for transcriptome-wide RNA structure probing using RNA-Seq, coupled with data analysis tools that allow quantitative determination of nuclease accessibility at single-base resolution. We provide a practical guide to designing and carrying out FragSeq experiments and data analysis. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 33% |
| Student > Ph. D. Student | 3 | 25% |
| Student > Bachelor | 2 | 17% |
| Student > Doctoral Student | 1 | 8% |
| Professor > Associate Professor | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 42% |
| Agricultural and Biological Sciences | 3 | 25% |
| Computer Science | 1 | 8% |
| Materials Science | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 13 January 2018.
All research outputs
#7,242,985
of 22,889,074 outputs
Outputs from Methods in molecular biology
#2,204
of 13,133 outputs
Outputs of similar age
#117,611
of 393,722 outputs
Outputs of similar age from Methods in molecular biology
#256
of 1,471 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 13,133 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 82% 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 393,722 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 69% of its contemporaries.
We're also able to compare this research output to 1,471 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.