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Article Metrics

Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics

Overview of attention for article published in Cell Systems, August 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
35 tweeters

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
50 Mendeley
Title
Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics
Published in
Cell Systems, August 2020
DOI 10.1016/j.cels.2020.06.013
Pubmed ID
Authors

Mi Yang, Francesca Petralia, Zhi Li, Hongyang Li, Weiping Ma, Xiaoyu Song, Sunkyu Kim, Heewon Lee, Han Yu, Bora Lee, Seohui Bae, Eunji Heo, Jan Kaczmarczyk, Piotr Stępniak, Michał Warchoł, Thomas Yu, Anna P. Calinawan, Paul C. Boutros, Samuel H. Payne, Boris Reva, Emily Boja, Henry Rodriguez, Gustavo Stolovitzky, Yuanfang Guan, Jaewoo Kang, Pei Wang, David Fenyö, Julio Saez-Rodriguez, Tunde Aderinwale, Ebrahim Afyounian, Piyush Agrawal, Mehreen Ali, Alicia Amadoz, Francisco Azuaje, John Bachman, Seohui Bae, Sherry Bhalla, José Carbonell-Caballero, Priyanka Chakraborty, Kumardeep Chaudhary, Yonghwa Choi, Yoonjung Choi, Cankut Çubuk, Sandeep Kumar Dhanda, Joaquín Dopazo, Laura L. Elo, Ábel Fóthi, Olivier Gevaert, Kirsi Granberg, Russell Greiner, Eunji Heo, Marta R. Hidalgo, Vivek Jayaswal, Hwisang Jeon, Minji Jeon, Sunil V. Kalmady, Yasuhiro Kambara, Jaewoo Kang, Keunsoo Kang, Tony Kaoma, Harpreet Kaur, Hilal Kazan, Devishi Kesar, Juha Kesseli, Daehan Kim, Keonwoo Kim, Sang-Yoon Kim, Sunkyu Kim, Sajal Kumar, Bora Lee, Heewon Lee, Yunpeng Liu, Roland Luethy, Swapnil Mahajan, Mehrad Mahmoudian, Arnaud Muller, Petr V. Nazarov, Hien Nguyen, Matti Nykter, Shujiro Okuda, Sungsoo Park, Gajendra Pal Singh Raghava, Jagath C. Rajapakse, Tommi Rantapero, Hobin Ryu, Francisco Salavert, Sohrab Saraei, Ruby Sharma, Ari Siitonen, Artem Sokolov, Kartik Subramanian, Veronika Suni, Tomi Suomi, Léon-Charles Tranchevent, Salman Sadullah Usmani, Tommi Välikangas, Roberto Vega, Hua Zhong

Twitter Demographics

The data shown below were collected from the profiles of 35 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 26%
Student > Ph. D. Student 10 20%
Student > Master 6 12%
Student > Doctoral Student 4 8%
Student > Bachelor 2 4%
Other 2 4%
Unknown 13 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 28%
Medicine and Dentistry 6 12%
Agricultural and Biological Sciences 5 10%
Computer Science 3 6%
Business, Management and Accounting 2 4%
Other 4 8%
Unknown 16 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 12 January 2021.
All research outputs
#1,166,948
of 18,203,597 outputs
Outputs from Cell Systems
#299
of 740 outputs
Outputs of similar age
#34,609
of 303,215 outputs
Outputs of similar age from Cell Systems
#16
of 30 outputs
Altmetric has tracked 18,203,597 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 740 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.8. This one has gotten more attention than average, scoring higher than 59% 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 303,215 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 30 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 50% of its contemporaries.