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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Candidate SNP Markers of Gender-Biased Autoimmune Complications of Monogenic Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters
|
|---|---|
| Published in |
Frontiers in immunology, April 2016
|
| DOI | 10.3389/fimmu.2016.00130 |
| Pubmed ID | |
| Authors |
Mikhail P. Ponomarenko, Olga Arkova, Dmitry Rasskazov, Petr Ponomarenko, Ludmila Savinkova, Nikolay Kolchanov |
| Abstract |
Some variations of human genome [for example, single nucleotide polymorphisms (SNPs)] are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis (double prevalence among women)]; rs11557611 [demyelinating diseases (thrice more prevalent among young white women than among non-white individuals)]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases (double prevalence among women)]; rs563763767 [Hughes syndrome-related thrombosis (lethal during pregnancy)]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 (all: autoimmune diseases underlying hypergammaglobulinemia in women). Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine. |
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 | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 28% |
| Researcher | 5 | 11% |
| Student > Postgraduate | 5 | 11% |
| Student > Bachelor | 4 | 9% |
| Other | 2 | 4% |
| Other | 5 | 11% |
| Unknown | 12 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 20% |
| Biochemistry, Genetics and Molecular Biology | 6 | 13% |
| Nursing and Health Professions | 4 | 9% |
| Immunology and Microbiology | 2 | 4% |
| Neuroscience | 2 | 4% |
| Other | 8 | 17% |
| Unknown | 15 | 33% |
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 20 April 2016.
All research outputs
#19,942,887
of 25,371,288 outputs
Outputs from Frontiers in immunology
#22,570
of 31,513 outputs
Outputs of similar age
#219,578
of 314,628 outputs
Outputs of similar age from Frontiers in immunology
#100
of 143 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,513 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 21st percentile – i.e., 21% 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 314,628 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.