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X Demographics
Mendeley readers
Attention Score in Context
Title |
The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles
|
---|---|
Published in |
Genome Biology, April 2023
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DOI | 10.1186/s13059-023-02915-y |
Pubmed ID | |
Authors |
Jacob Schreiber, Carles Boix, Jin wook Lee, Hongyang Li, Yuanfang Guan, Chun-Chieh Chang, Jen-Chien Chang, Alex Hawkins-Hooker, Bernhard Schölkopf, Gabriele Schweikert, Mateo Rojas Carulla, Arif Canakoglu, Francesco Guzzo, Luca Nanni, Marco Masseroli, Mark James Carman, Pietro Pinoli, Chenyang Hong, Kevin Y. Yip, Jeffrey P. Spence, Sanjit Singh Batra, Yun S. Song, Shaun Mahony, Zheng Zhang, Wuwei Tan, Yang Shen, Yuanfei Sun, Minyi Shi, Jessika Adrian, Richard Sandstrom, Nina Farrell, Jessica Halow, Kristen Lee, Lixia Jiang, Xinqiong Yang, Charles Epstein, J. Seth Strattan, Bradley Bernstein, Michael Snyder, Manolis Kellis, William Stafford, Anshul Kundaje |
X Demographics
The data shown below were collected from the profiles of 41 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 | 17 | 41% |
United Kingdom | 7 | 17% |
Japan | 2 | 5% |
India | 1 | 2% |
Canada | 1 | 2% |
France | 1 | 2% |
Germany | 1 | 2% |
Unknown | 11 | 27% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 20 | 49% |
Scientists | 19 | 46% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 15 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 13% |
Other | 1 | 7% |
Professor | 1 | 7% |
Student > Bachelor | 1 | 7% |
Student > Ph. D. Student | 1 | 7% |
Other | 1 | 7% |
Unknown | 8 | 53% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 27% |
Computer Science | 2 | 13% |
Agricultural and Biological Sciences | 1 | 7% |
Engineering | 1 | 7% |
Unknown | 7 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 14 August 2023.
All research outputs
#1,876,391
of 25,515,042 outputs
Outputs from Genome Biology
#1,563
of 4,484 outputs
Outputs of similar age
#37,435
of 414,250 outputs
Outputs of similar age from Genome Biology
#33
of 89 outputs
Altmetric has tracked 25,515,042 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,484 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 65% 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 414,250 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 90% of its contemporaries.
We're also able to compare this research output to 89 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 64% of its contemporaries.