You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
DeepT3_4: A Hybrid Deep Neural Network Model for the Distinction Between Bacterial Type III and IV Secreted Effectors
|
|---|---|
| Published in |
Frontiers in Microbiology, January 2021
|
| DOI | 10.3389/fmicb.2021.605782 |
| Pubmed ID | |
| Authors |
Lezheng Yu, Fengjuan Liu, Yizhou Li, Jiesi Luo, Runyu Jing |
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 % |
|---|---|---|
| Switzerland | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 25% |
| Student > Ph. D. Student | 2 | 13% |
| Student > Master | 2 | 13% |
| Student > Doctoral Student | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 4 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 25% |
| Computer Science | 2 | 13% |
| Agricultural and Biological Sciences | 1 | 6% |
| Immunology and Microbiology | 1 | 6% |
| Engineering | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 7 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 15 March 2021.
All research outputs
#15,134,382
of 23,274,744 outputs
Outputs from Frontiers in Microbiology
#14,169
of 25,556 outputs
Outputs of similar age
#289,034
of 503,712 outputs
Outputs of similar age from Frontiers in Microbiology
#529
of 934 outputs
Altmetric has tracked 23,274,744 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25,556 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 39th percentile – i.e., 39% 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 503,712 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 934 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.