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Mendeley readers
Attention Score in Context
Chapter title |
Comprehensive HLA Typing from a Current Allele Database Using Next-Generation Sequencing Data
|
---|---|
Chapter number | 16 |
Book title |
HLA Typing
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-8546-3_16 |
Pubmed ID | |
Book ISBNs |
978-1-4939-8545-6, 978-1-4939-8546-3
|
Authors |
Shuji Kawaguchi, Koichiro Higasa, Ryo Yamada, Fumihiko Matsuda, Kawaguchi, Shuji, Higasa, Koichiro, Yamada, Ryo, Matsuda, Fumihiko |
Abstract |
HLA allele information is essential for a variety of medical applications, such as genomic studies of multifactorial diseases, including immune system and inflammation-related disorders, and donor selection in organ transplantation and regenerative medicine. To obtain this information, an accurate HLA typing method that is applicable for any allele registered in HLA allele databases is needed. Here, we describe a method for determining alleles from a current HLA database using next-generation sequencing (NGS) results. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 67% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 67% |
Members of the public | 1 | 33% |
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 % |
---|---|---|
Unknown | 12 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 3 | 25% |
Student > Ph. D. Student | 2 | 17% |
Student > Master | 2 | 17% |
Professor | 1 | 8% |
Other | 1 | 8% |
Other | 0 | 0% |
Unknown | 3 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 5 | 42% |
Agricultural and Biological Sciences | 2 | 17% |
Medicine and Dentistry | 2 | 17% |
Unknown | 3 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 August 2018.
All research outputs
#15,009,334
of 23,088,369 outputs
Outputs from Methods in molecular biology
#4,749
of 13,206 outputs
Outputs of similar age
#256,079
of 442,629 outputs
Outputs of similar age from Methods in molecular biology
#508
of 1,499 outputs
Altmetric has tracked 23,088,369 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,206 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 59% 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 442,629 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.