| Title |
Leveraging Systematic Functional Analysis to Benchmark an In Silico Framework Distinguishes Driver from Passenger MEK Mutants in Cancer
|
|---|---|
| Published in |
Cancer Research, October 2020
|
| DOI | 10.1158/0008-5472.can-20-0865 |
| Pubmed ID | |
| Authors |
Aphrothiti J Hanrahan, Brooke E Sylvester, Matthew T Chang, Arijh Elzein, Jianjiong Gao, Weiwei Han, Ye Liu, Dong Xu, Sizhi P Gao, Alexander N Gorelick, Alexis M Jones, Amber J Kiliti, Moriah H Nissan, Clare A Nimura, Abigail N Poteshman, Zhan Yao, Yijun Gao, Wenhuo Hu, Hannah C Wise, Elena I Gavrila, Alexander N Shoushtari, Shakuntala Tiwari, Agnes Viale, Omar Abdel-Wahab, Taha Merghoub, Michael F Berger, Neal Rosen, Barry S Taylor, David B Solit |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 14 | 61% |
| United Kingdom | 2 | 9% |
| Japan | 1 | 4% |
| Germany | 1 | 4% |
| France | 1 | 4% |
| Unknown | 4 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 52% |
| Scientists | 8 | 35% |
| Science communicators (journalists, bloggers, editors) | 2 | 9% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 24% |
| Student > Ph. D. Student | 4 | 12% |
| Student > Bachelor | 2 | 6% |
| Professor | 2 | 6% |
| Other | 2 | 6% |
| Other | 4 | 12% |
| Unknown | 12 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 26% |
| Medicine and Dentistry | 6 | 18% |
| Linguistics | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Environmental Science | 1 | 3% |
| Other | 4 | 12% |
| Unknown | 12 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 121. 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 August 2021.
All research outputs
#306,848
of 23,567,572 outputs
Outputs from Cancer Research
#155
of 18,389 outputs
Outputs of similar age
#9,765
of 413,624 outputs
Outputs of similar age from Cancer Research
#4
of 157 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,389 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has done particularly well, scoring higher than 99% 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 413,624 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 97% of its contemporaries.
We're also able to compare this research output to 157 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 97% of its contemporaries.