Title |
Single-cell epigenomics: powerful new methods for understanding gene regulation and cell identity
|
---|---|
Published in |
Genome Biology, April 2016
|
DOI | 10.1186/s13059-016-0944-x |
Pubmed ID | |
Authors |
Stephen J. Clark, Heather J. Lee, Sébastien A. Smallwood, Gavin Kelsey, Wolf Reik |
Abstract |
Emerging single-cell epigenomic methods are being developed with the exciting potential to transform our knowledge of gene regulation. Here we review available techniques and future possibilities, arguing that the full potential of single-cell epigenetic studies will be realized through parallel profiling of genomic, transcriptional, and epigenetic information. |
X Demographics
The data shown below were collected from the profiles of 56 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 Kingdom | 14 | 25% |
United States | 10 | 18% |
Japan | 2 | 4% |
Spain | 2 | 4% |
Belgium | 2 | 4% |
France | 2 | 4% |
Canada | 1 | 2% |
Germany | 1 | 2% |
Peru | 1 | 2% |
Other | 1 | 2% |
Unknown | 20 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 27 | 48% |
Members of the public | 26 | 46% |
Science communicators (journalists, bloggers, editors) | 3 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 692 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 6 | <1% |
United States | 4 | <1% |
Germany | 2 | <1% |
France | 2 | <1% |
Brazil | 1 | <1% |
Czechia | 1 | <1% |
Korea, Republic of | 1 | <1% |
Denmark | 1 | <1% |
Netherlands | 1 | <1% |
Other | 2 | <1% |
Unknown | 671 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 189 | 27% |
Researcher | 135 | 20% |
Student > Master | 70 | 10% |
Student > Bachelor | 56 | 8% |
Student > Doctoral Student | 39 | 6% |
Other | 98 | 14% |
Unknown | 105 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 212 | 31% |
Agricultural and Biological Sciences | 180 | 26% |
Medicine and Dentistry | 43 | 6% |
Computer Science | 26 | 4% |
Engineering | 23 | 3% |
Other | 79 | 11% |
Unknown | 129 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 49. 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 19 March 2024.
All research outputs
#869,164
of 25,692,343 outputs
Outputs from Genome Biology
#577
of 4,502 outputs
Outputs of similar age
#15,120
of 314,411 outputs
Outputs of similar age from Genome Biology
#13
of 77 outputs
Altmetric has tracked 25,692,343 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 4,502 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has done well, scoring higher than 87% 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 314,411 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 95% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.