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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation
|
|---|---|
| Published in |
Journal of Translational Medicine, November 2020
|
| DOI | 10.1186/s12967-020-02602-7 |
| Pubmed ID | |
| Authors |
Yihan Zhao, Kai Zheng, Baoyi Guan, Mengmeng Guo, Lei Song, Jie Gao, Hua Qu, Yuhui Wang, Dazhuo Shi, Ying Zhang |
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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 23% |
| Student > Bachelor | 3 | 10% |
| Researcher | 3 | 10% |
| Student > Master | 3 | 10% |
| Professor | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 11 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 16% |
| Engineering | 4 | 13% |
| Computer Science | 3 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Medicine and Dentistry | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 12 | 39% |
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 17 November 2020.
All research outputs
#19,017,658
of 23,577,761 outputs
Outputs from Journal of Translational Medicine
#3,088
of 4,186 outputs
Outputs of similar age
#312,044
of 415,549 outputs
Outputs of similar age from Journal of Translational Medicine
#67
of 91 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,186 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 16th percentile – i.e., 16% 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 415,549 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.