Title |
MetaCell: analysis of single-cell RNA-seq data using K-nn graph partitions
|
---|---|
Published in |
Genome Biology, October 2019
|
DOI | 10.1186/s13059-019-1812-2 |
Pubmed ID | |
Authors |
Yael Baran, Akhiad Bercovich, Arnau Sebe-Pedros, Yaniv Lubling, Amir Giladi, Elad Chomsky, Zohar Meir, Michael Hoichman, Aviezer Lifshitz, Amos Tanay |
X Demographics
The data shown below were collected from the profiles of 43 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 | 10 | 23% |
United Kingdom | 4 | 9% |
Switzerland | 2 | 5% |
Spain | 2 | 5% |
Hong Kong | 1 | 2% |
Austria | 1 | 2% |
France | 1 | 2% |
Mexico | 1 | 2% |
Japan | 1 | 2% |
Other | 4 | 9% |
Unknown | 16 | 37% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 23 | 53% |
Scientists | 19 | 44% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 484 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 484 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 111 | 23% |
Researcher | 90 | 19% |
Student > Master | 55 | 11% |
Student > Bachelor | 37 | 8% |
Student > Postgraduate | 15 | 3% |
Other | 46 | 10% |
Unknown | 130 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 151 | 31% |
Agricultural and Biological Sciences | 58 | 12% |
Computer Science | 37 | 8% |
Immunology and Microbiology | 32 | 7% |
Medicine and Dentistry | 15 | 3% |
Other | 49 | 10% |
Unknown | 142 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 46. 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 09 May 2024.
All research outputs
#926,937
of 25,874,560 outputs
Outputs from Genome Biology
#622
of 4,528 outputs
Outputs of similar age
#20,042
of 369,717 outputs
Outputs of similar age from Genome Biology
#16
of 74 outputs
Altmetric has tracked 25,874,560 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,528 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 done well, scoring higher than 86% 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 369,717 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 94% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.