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Michigan Publishing

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

Overview of attention for article published in Cell Systems, July 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 (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

twitter
52 X users

Citations

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20 Dimensions

Readers on

mendeley
76 Mendeley
Title
Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics
Published in
Cell Systems, July 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, NCI-CPTAC-DREAM Consortium, 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, Emily Boja, Henry Rodriguez, Gustavo Stolovitzky, Yuanfang Guan, Jaewoo Kang, Pei Wang, David Fenyö, Julio Saez-Rodriguez

X Demographics

X Demographics

The data shown below were collected from the profiles of 52 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 22%
Student > Ph. D. Student 16 21%
Student > Master 9 12%
Professor 3 4%
Student > Doctoral Student 3 4%
Other 7 9%
Unknown 21 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 30%
Agricultural and Biological Sciences 8 11%
Medicine and Dentistry 6 8%
Computer Science 5 7%
Business, Management and Accounting 2 3%
Other 7 9%
Unknown 25 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 13 May 2023.
All research outputs
#1,290,491
of 25,608,265 outputs
Outputs from Cell Systems
#296
of 988 outputs
Outputs of similar age
#36,277
of 428,545 outputs
Outputs of similar age from Cell Systems
#15
of 32 outputs
Altmetric has tracked 25,608,265 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 988 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.1. This one has gotten more attention than average, scoring higher than 70% 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 428,545 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 32 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 56% of its contemporaries.