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X Demographics
Mendeley readers
Attention Score in Context
| Title |
neoDL: a novel neoantigen intrinsic feature-based deep learning model identifies IDH wild-type glioblastomas with the longest survival
|
|---|---|
| Published in |
BMC Bioinformatics, July 2021
|
| DOI | 10.1186/s12859-021-04301-6 |
| Pubmed ID | |
| Authors |
Ting Sun, Yufei He, Wendong Li, Guang Liu, Lin Li, Lu Wang, Zixuan Xiao, Xiaohan Han, Hao Wen, Yong Liu, Yifan Chen, Haoyu Wang, Jing Li, Yubo Fan, Wei Zhang, Jing Zhang |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 20% |
| Sweden | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 28% |
| Lecturer | 1 | 6% |
| Other | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 7 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 17% |
| Agricultural and Biological Sciences | 2 | 11% |
| Computer Science | 2 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Neuroscience | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 8 | 44% |
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 July 2021.
All research outputs
#13,527,742
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#4,095
of 7,388 outputs
Outputs of similar age
#188,117
of 436,288 outputs
Outputs of similar age from BMC Bioinformatics
#73
of 106 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 42nd percentile – i.e., 42% 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 436,288 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 55% of its contemporaries.
We're also able to compare this research output to 106 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.