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X Demographics
Mendeley readers
Attention Score in Context
Title |
Splicing heterogeneity: separating signal from noise
|
---|---|
Published in |
Genome Biology, July 2018
|
DOI | 10.1186/s13059-018-1467-4 |
Pubmed ID | |
Authors |
Yihan Wan, Daniel R. Larson |
Abstract |
Single-cell analyses have revealed a tremendous variety among cells in the abundance and chemical composition of RNA. Much of this heterogeneity is due to alternative splicing by the spliceosome. Little is known about how many of the resulting isoforms are biologically functional or just provide noise with little to no impact. The dynamic nature of the spliceosome provides numerous opportunities for regulation but is also the source of stochastic fluctuations. We discuss possible origins of splicing stochasticity, the experimental approaches for studying heterogeneity in isoforms, and the potential biological significance of noisy splicing in development and disease. |
X Demographics
The data shown below were collected from the profiles of 25 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 | 4 | 16% |
United States | 3 | 12% |
Germany | 2 | 8% |
France | 2 | 8% |
Spain | 1 | 4% |
Canada | 1 | 4% |
Australia | 1 | 4% |
Unknown | 11 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 48% |
Scientists | 11 | 44% |
Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 104 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 32 | 31% |
Researcher | 17 | 16% |
Student > Master | 11 | 11% |
Student > Bachelor | 9 | 9% |
Student > Doctoral Student | 5 | 5% |
Other | 9 | 9% |
Unknown | 21 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 44 | 42% |
Agricultural and Biological Sciences | 26 | 25% |
Computer Science | 3 | 3% |
Medicine and Dentistry | 2 | 2% |
Engineering | 2 | 2% |
Other | 6 | 6% |
Unknown | 21 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 01 June 2023.
All research outputs
#2,283,565
of 25,385,509 outputs
Outputs from Genome Biology
#1,883
of 4,468 outputs
Outputs of similar age
#45,460
of 339,673 outputs
Outputs of similar age from Genome Biology
#43
of 61 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 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 57% 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 339,673 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.