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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Convolutional neural network based on SMILES representation of compounds for detecting chemical motif
|
|---|---|
| Published in |
BMC Bioinformatics, December 2018
|
| DOI | 10.1186/s12859-018-2523-5 |
| Pubmed ID | |
| Authors |
Maya Hirohara, Yutaka Saito, Yuki Koda, Kengo Sato, Yasubumi Sakakibara |
X Demographics
The data shown below were collected from the profiles of 21 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 8 | 38% |
| France | 2 | 10% |
| United States | 1 | 5% |
| Unknown | 10 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 18 | 86% |
| Scientists | 3 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 230 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 230 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 38 | 17% |
| Student > Master | 31 | 13% |
| Student > Bachelor | 30 | 13% |
| Researcher | 28 | 12% |
| Student > Doctoral Student | 12 | 5% |
| Other | 21 | 9% |
| Unknown | 70 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 43 | 19% |
| Computer Science | 32 | 14% |
| Biochemistry, Genetics and Molecular Biology | 19 | 8% |
| Engineering | 16 | 7% |
| Chemical Engineering | 10 | 4% |
| Other | 33 | 14% |
| Unknown | 77 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 05 April 2021.
All research outputs
#1,560,235
of 24,226,848 outputs
Outputs from BMC Bioinformatics
#273
of 7,512 outputs
Outputs of similar age
#36,920
of 445,428 outputs
Outputs of similar age from BMC Bioinformatics
#11
of 216 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,512 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 96% 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 445,428 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.