You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A modified TALEN-based system for robust generation of knock-out human pluripotent stem cell lines and disease models
|
|---|---|
| Published in |
BMC Genomics, November 2013
|
| DOI | 10.1186/1471-2164-14-773 |
| Pubmed ID | |
| Authors |
Stefan Frank, Boris V Skryabin, Boris Greber |
| Abstract |
Transcription activator-like effector nucleases (TALENs) have emerged as a tool for enabling targeted gene editing and disruption in difficult systems, such as human pluripotent stem cells (hPSCs). The modular architecture of TAL effectors theoretically enables targeting of any genomic locus and several cloning systems for custom TALEN assembly have recently been established. However, there is a lack of versatile TALEN expression systems applicable to hPSCs. |
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 % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Germany | 1 | 1% |
| Italy | 1 | 1% |
| France | 1 | 1% |
| United Kingdom | 1 | 1% |
| Poland | 1 | 1% |
| Unknown | 67 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 28 | 38% |
| Student > Ph. D. Student | 19 | 26% |
| Student > Master | 5 | 7% |
| Student > Postgraduate | 4 | 5% |
| Student > Bachelor | 4 | 5% |
| Other | 6 | 8% |
| Unknown | 8 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 34 | 46% |
| Biochemistry, Genetics and Molecular Biology | 17 | 23% |
| Neuroscience | 5 | 7% |
| Medicine and Dentistry | 4 | 5% |
| Engineering | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 9 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 30 June 2022.
All research outputs
#2,883,563
of 24,293,076 outputs
Outputs from BMC Genomics
#921
of 10,943 outputs
Outputs of similar age
#26,617
of 220,333 outputs
Outputs of similar age from BMC Genomics
#12
of 152 outputs
Altmetric has tracked 24,293,076 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,943 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 91% 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 220,333 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 152 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 92% of its contemporaries.