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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Current State and Future of CRISPR-Cas9 gRNA Design Tools
|
|---|---|
| Published in |
Frontiers in Pharmacology, July 2018
|
| DOI | 10.3389/fphar.2018.00749 |
| Pubmed ID | |
| Authors |
Laurence O. W. Wilson, Aidan R. O’Brien, Denis C. Bauer |
| Abstract |
Recent years have seen the development of computational tools to assist researchers in performing CRISPR-Cas9 experiment optimally. More specifically, these tools aim to maximize on-target activity (guide efficiency) while also minimizing potential off-target effects (guide specificity) by analyzing the features of the target site. Nonetheless, currently available tools cannot robustly predict experimental success as prediction accuracy depends on the approximations of the underlying model and how closely the experimental setup matches the data the model was trained on. Here, we present an overview of the available computational tools, their current limitations and future considerations. We discuss new trends around personalized health by taking genomic variants into account when predicting target sites as well as discussing other governing factors that can improve prediction accuracy. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | 17% |
| United Kingdom | 1 | 8% |
| Unknown | 9 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 5 | 42% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 276 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 276 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 53 | 19% |
| Student > Ph. D. Student | 51 | 18% |
| Student > Master | 28 | 10% |
| Researcher | 26 | 9% |
| Student > Doctoral Student | 15 | 5% |
| Other | 25 | 9% |
| Unknown | 78 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 80 | 29% |
| Agricultural and Biological Sciences | 53 | 19% |
| Medicine and Dentistry | 16 | 6% |
| Chemistry | 7 | 3% |
| Computer Science | 5 | 2% |
| Other | 34 | 12% |
| Unknown | 81 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 20 March 2022.
All research outputs
#2,122,484
of 23,419,482 outputs
Outputs from Frontiers in Pharmacology
#796
of 16,943 outputs
Outputs of similar age
#45,249
of 327,760 outputs
Outputs of similar age from Frontiers in Pharmacology
#23
of 397 outputs
Altmetric has tracked 23,419,482 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,943 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 95% 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 327,760 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 86% of its contemporaries.
We're also able to compare this research output to 397 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 94% of its contemporaries.