| Title |
A Network Pharmacology-Based Strategy For Predicting Active Ingredients And Potential Targets Of LiuWei DiHuang Pill In Treating Type 2 Diabetes Mellitus
|
|---|---|
| Published in |
Drug Design, Development and Therapy, November 2019
|
| DOI | 10.2147/dddt.s216644 |
| Pubmed ID | |
| Authors |
Dan He, Jian-Hua Huang, Zhe-Yu Zhang, Qing Du, Wei-Jun Peng, Rong Yu, Si-Fang Zhang, Shui-Han Zhang, Yu-Hui Qin |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 13% |
| Student > Master | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Lecturer | 2 | 4% |
| Researcher | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 27 | 56% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 8% |
| Agricultural and Biological Sciences | 3 | 6% |
| Arts and Humanities | 2 | 4% |
| Nursing and Health Professions | 2 | 4% |
| Social Sciences | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 30 | 63% |
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 04 June 2020.
All research outputs
#21,011,157
of 25,806,080 outputs
Outputs from Drug Design, Development and Therapy
#1,462
of 2,283 outputs
Outputs of similar age
#290,049
of 379,599 outputs
Outputs of similar age from Drug Design, Development and Therapy
#17
of 32 outputs
Altmetric has tracked 25,806,080 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,283 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 22nd percentile – i.e., 22% 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 379,599 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.