Review of CRISPR/Cas9 sgRNA Design Tools
Interdisciplinary Sciences – Computational Life Sciences, ISSN: 1867-1462, Vol: 10, Issue: 2, Page: 455-465
2018
- 202Citations
- 719Captures
- 1Mentions
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations202
- Citation Indexes182
- 182
- CrossRef8
- Patent Family Citations18
- Patent Families18
- Policy Citations2
- Policy Citation2
- Captures719
- Readers719
- 719
- Mentions1
- News Mentions1
- News1
Review Description
The adaptive immunity system in bacteria and archaea, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-associate (CRISPR/Cas), has been adapted as a powerful gene editing tool and got a broad application in genome research field due to its ease of use and cost-effectiveness. The performance of CRISPR/Cas relies on well-designed single-guide RNA (sgRNA), so a lot of bioinformatic tools have been developed to assist the design of highly active and specific sgRNA. These tools vary in design specifications, parameters, genomes and so on. To help researchers to choose their proper tools, we reviewed various sgRNA design tools, mainly focusing on their on-target efficiency prediction model and off-target detection algorithm.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85046878848&origin=inward; http://dx.doi.org/10.1007/s12539-018-0298-z; http://www.ncbi.nlm.nih.gov/pubmed/29644494; http://link.springer.com/10.1007/s12539-018-0298-z; https://dx.doi.org/10.1007/s12539-018-0298-z; https://link.springer.com/article/10.1007/s12539-018-0298-z
Springer Nature
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