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Attention Score in Context
Chapter title |
Generation of FLIP and FLIP-FlpE Targeting Vectors for Biallelic Conditional and Reversible Gene Knockouts in Mouse and Human Cells
|
---|---|
Chapter number | 19 |
Book title |
Somatic Stem Cells
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Published in |
Methods in molecular biology, September 2018
|
DOI | 10.1007/978-1-4939-8697-2_19 |
Pubmed ID | |
Book ISBNs |
978-1-4939-8696-5, 978-1-4939-8697-2
|
Authors |
Bon-Kyoung Koo, Koo, Bon-Kyoung |
Abstract |
Rapid generation of conditional knockout models in a diploid system is challenging. Recently, CRISPR-FLIP strategy has been introduced, which facilitates the generation of biallelic conditional or reversible gene knockouts in various mammalian cell lines including mouse and human pluripotent stem cells by codelivery of the CRISPR/Cas9 system and a universal intronic cassette-FLIP and FLIP-FlpE. Here, I describe the design and cloning method of FLIP and FLIP-FlpE targeting vectors for conditional and reversible gene knockouts. This method is applicable to mouse embryonic stem cells, human induced pluripotent stem cells, and adult stem cell-derived organoids. |
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 % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 19 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 4 | 21% |
Student > Ph. D. Student | 3 | 16% |
Student > Bachelor | 2 | 11% |
Student > Master | 1 | 5% |
Librarian | 1 | 5% |
Other | 0 | 0% |
Unknown | 8 | 42% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 21% |
Agricultural and Biological Sciences | 3 | 16% |
Neuroscience | 2 | 11% |
Immunology and Microbiology | 1 | 5% |
Engineering | 1 | 5% |
Other | 0 | 0% |
Unknown | 8 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 10 September 2018.
All research outputs
#15,545,423
of 23,103,436 outputs
Outputs from Methods in molecular biology
#5,412
of 13,208 outputs
Outputs of similar age
#212,770
of 336,598 outputs
Outputs of similar age from Methods in molecular biology
#97
of 247 outputs
Altmetric has tracked 23,103,436 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,208 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 336,598 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 247 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.