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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detecting early-warning signals of type 1 diabetes and its leading biomolecular networks by dynamical network biomarkers
|
|---|---|
| Published in |
BMC Medical Genomics, May 2013
|
| DOI | 10.1186/1755-8794-6-s2-s8 |
| Pubmed ID | |
| Authors |
Xiaoping Liu, Rui Liu, Xing-Ming Zhao, Luonan Chen |
| Abstract |
Type 1 diabetes (T1D) is a complex disease and harmful to human health, and most of the existing biomarkers are mainly to measure the disease phenotype after the disease onset (or drastic deterioration). Until now, there is no effective biomarker which can predict the upcoming disease (or pre-disease state) before disease onset or disease deterioration. Further, the detail molecular mechanism for such deterioration of the disease, e.g., driver genes or causal network of the disease, is still unclear. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Luxembourg | 2 | 3% |
| Korea, Republic of | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 76 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 23% |
| Researcher | 16 | 20% |
| Student > Bachelor | 9 | 11% |
| Student > Master | 9 | 11% |
| Student > Postgraduate | 4 | 5% |
| Other | 9 | 11% |
| Unknown | 15 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 19% |
| Agricultural and Biological Sciences | 11 | 14% |
| Biochemistry, Genetics and Molecular Biology | 11 | 14% |
| Computer Science | 6 | 8% |
| Engineering | 5 | 6% |
| Other | 15 | 19% |
| Unknown | 17 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 24 May 2013.
All research outputs
#7,428,447
of 22,709,015 outputs
Outputs from BMC Medical Genomics
#359
of 1,215 outputs
Outputs of similar age
#65,160
of 193,543 outputs
Outputs of similar age from BMC Medical Genomics
#5
of 16 outputs
Altmetric has tracked 22,709,015 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,215 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 66% 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 193,543 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 16 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 68% of its contemporaries.