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Mendeley readers
Attention Score in Context
| Title |
A powerful statistical method identifies novel loci associated with diastolic blood pressure triggered by nonlinear gene-environment interaction
|
|---|---|
| Published in |
BMC Proceedings, June 2014
|
| DOI | 10.1186/1753-6561-8-s1-s61 |
| Pubmed ID | |
| Authors |
Honglang Wang, Tao He, Cen Wu, Ping-Shou Zhong, Yuehua Cui |
| Abstract |
The genetic basis of blood pressure often involves multiple genetic factors and their interactions with environmental factors. Gene-environment interaction is assumed to play an important role in determining individual blood pressure variability. Older people are more prone to high blood pressure than younger ones and the risk may not display a linear trend over the life span. However, which gene shows sensitivity to aging in its effect on blood pressure is not clear. In this work, we allowed the genetic effect to vary over time and propose a varying-coefficient model to identify potential genetic players that show nonlinear response across different age stages. We detected 2 novel loci, gene MIR1263 (a microRNA coding gene) on chromosome 3 and gene UNC13B on chromosome 9, that are nonlinearly associated with diastolic blood pressure. Further experimental validation is needed to confirm this finding. |
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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 20% |
| Researcher | 2 | 20% |
| Student > Master | 1 | 10% |
| Other | 1 | 10% |
| Professor > Associate Professor | 1 | 10% |
| Other | 1 | 10% |
| Unknown | 2 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 20% |
| Agricultural and Biological Sciences | 2 | 20% |
| Mathematics | 1 | 10% |
| Psychology | 1 | 10% |
| Medicine and Dentistry | 1 | 10% |
| Other | 0 | 0% |
| Unknown | 3 | 30% |
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 19 December 2014.
All research outputs
#20,247,117
of 22,775,504 outputs
Outputs from BMC Proceedings
#318
of 374 outputs
Outputs of similar age
#192,552
of 228,203 outputs
Outputs of similar age from BMC Proceedings
#19
of 21 outputs
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So far Altmetric has tracked 374 research outputs from this source. They receive a mean Attention Score of 4.0. 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 21 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.