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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic dissection of NK cell responses
|
|---|---|
| Published in |
Frontiers in immunology, January 2013
|
| DOI | 10.3389/fimmu.2012.00425 |
| Pubmed ID | |
| Authors |
Peter Moussa, Jennifer Marton, Silvia M. Vidal, Nassima Fodil-Cornu |
| Abstract |
The association of Natural Killer (NK) cell deficiencies with disease susceptibility has established a central role for NK cells in host defence. In this context, genetic approaches have been pivotal in elucidating and characterizing the molecular mechanisms underlying NK cell function. To this end, homozygosity mapping and linkage analysis in humans have identified mutations that impact NK cell function and cause life-threatening diseases. However, several critical restrictions accompany genetic studies in humans. Studying NK cell pathophysiology in a mouse model has therefore proven a useful tool. The relevance of the mouse model is underscored by the similarities that exist between cell-structure-sensing receptors and the downstream signaling that leads to NK cell activation. In this review, we provide an overview of how human and mouse quantitative trait locis (QTLs) have facilitated the identification of genes that modulate NK cell development, recognition, and killing of target cells. |
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 % |
|---|---|---|
| Switzerland | 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 21% |
| Student > Master | 6 | 16% |
| Student > Bachelor | 5 | 13% |
| Researcher | 4 | 11% |
| Student > Doctoral Student | 4 | 11% |
| Other | 4 | 11% |
| Unknown | 7 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 39% |
| Biochemistry, Genetics and Molecular Biology | 5 | 13% |
| Immunology and Microbiology | 5 | 13% |
| Medicine and Dentistry | 4 | 11% |
| Computer Science | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 18% |
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 18 January 2013.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from Frontiers in immunology
#27,417
of 31,516 outputs
Outputs of similar age
#258,412
of 288,991 outputs
Outputs of similar age from Frontiers in immunology
#335
of 503 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,516 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 503 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.