| Title |
Multi-omic single-cell velocity models epigenome–transcriptome interactions and improves cell fate prediction
|
|---|---|
| Published in |
Nature Biotechnology, October 2022
|
| DOI | 10.1038/s41587-022-01476-y |
| Pubmed ID | |
| Authors |
Chen Li, Maria C. Virgilio, Kathleen L. Collins, Joshua D. Welch |
X Demographics
The data shown below were collected from the profiles of 202 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 | 57 | 28% |
| Germany | 9 | 4% |
| United Kingdom | 8 | 4% |
| Sweden | 5 | 2% |
| Australia | 5 | 2% |
| Japan | 3 | 1% |
| Spain | 3 | 1% |
| Italy | 3 | 1% |
| Canada | 3 | 1% |
| Other | 20 | 10% |
| Unknown | 86 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 105 | 52% |
| Scientists | 89 | 44% |
| Practitioners (doctors, other healthcare professionals) | 5 | 2% |
| Science communicators (journalists, bloggers, editors) | 3 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 144 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 144 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 18% |
| Researcher | 21 | 15% |
| Student > Bachelor | 14 | 10% |
| Student > Postgraduate | 9 | 6% |
| Student > Master | 7 | 5% |
| Other | 18 | 13% |
| Unknown | 49 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 44 | 31% |
| Agricultural and Biological Sciences | 14 | 10% |
| Neuroscience | 6 | 4% |
| Immunology and Microbiology | 6 | 4% |
| Medicine and Dentistry | 6 | 4% |
| Other | 18 | 13% |
| Unknown | 50 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 175. 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
#238,178
of 25,920,652 outputs
Outputs from Nature Biotechnology
#502
of 8,642 outputs
Outputs of similar age
#6,546
of 441,334 outputs
Outputs of similar age from Nature Biotechnology
#18
of 128 outputs
Altmetric has tracked 25,920,652 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,642 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.6. This one has done particularly well, scoring higher than 94% 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 441,334 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 98% of its contemporaries.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.