| Title |
Predicting tumor cell line response to drug pairs with deep learning
|
|---|---|
| Published in |
BMC Bioinformatics, December 2018
|
| DOI | 10.1186/s12859-018-2509-3 |
| Pubmed ID | |
| Authors |
Fangfang Xia, Maulik Shukla, Thomas Brettin, Cristina Garcia-Cardona, Judith Cohn, Jonathan E. Allen, Sergei Maslov, Susan L. Holbeck, James H. Doroshow, Yvonne A. Evrard, Eric A. Stahlberg, Rick L. Stevens |
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 % |
|---|---|---|
| United Kingdom | 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 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 120 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 18% |
| Student > Ph. D. Student | 20 | 17% |
| Student > Master | 13 | 11% |
| Student > Bachelor | 11 | 9% |
| Other | 6 | 5% |
| Other | 12 | 10% |
| Unknown | 37 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 23 | 19% |
| Computer Science | 20 | 17% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 5% |
| Engineering | 6 | 5% |
| Agricultural and Biological Sciences | 6 | 5% |
| Other | 15 | 13% |
| Unknown | 44 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 18 January 2024.
All research outputs
#7,916,590
of 25,323,244 outputs
Outputs from BMC Bioinformatics
#2,865
of 7,672 outputs
Outputs of similar age
#150,239
of 449,025 outputs
Outputs of similar age from BMC Bioinformatics
#77
of 206 outputs
Altmetric has tracked 25,323,244 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,672 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 gotten more attention than average, scoring higher than 60% 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 449,025 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 65% of its contemporaries.
We're also able to compare this research output to 206 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.