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Mendeley readers
Attention Score in Context
| Title |
Switches, Excitable Responses and Oscillations in the Ring1B/Bmi1 Ubiquitination System
|
|---|---|
| Published in |
PLoS Computational Biology, December 2011
|
| DOI | 10.1371/journal.pcbi.1002317 |
| Pubmed ID | |
| Authors |
Lan K. Nguyen, Javier Muñoz-García, Helene Maccario, Aaron Ciechanover, Walter Kolch, Boris N. Kholodenko |
| Abstract |
In an active, self-ubiquitinated state, the Ring1B ligase monoubiquitinates histone H2A playing a critical role in Polycomb-mediated gene silencing. Following ubiquitination by external ligases, Ring1B is targeted for proteosomal degradation. Using biochemical data and computational modeling, we show that the Ring1B ligase can exhibit abrupt switches, overshoot transitions and self-perpetuating oscillations between its distinct ubiquitination and activity states. These different Ring1B states display canonical or multiply branched, atypical polyubiquitin chains and involve association with the Polycomb-group protein Bmi1. Bistable switches and oscillations may lead to all-or-none histone H2A monoubiquitination rates and result in discrete periods of gene (in)activity. Switches, overshoots and oscillations in Ring1B catalytic activity and proteosomal degradation are controlled by the abundances of Bmi1 and Ring1B, and the activities and abundances of external ligases and deubiquitinases, such as E6-AP and USP7. |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Ireland | 2 | 3% |
| China | 1 | 2% |
| Unknown | 54 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 27% |
| Researcher | 15 | 25% |
| Student > Master | 8 | 14% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 3 | 5% |
| Other | 3 | 5% |
| Unknown | 9 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 41% |
| Biochemistry, Genetics and Molecular Biology | 15 | 25% |
| Medicine and Dentistry | 3 | 5% |
| Computer Science | 1 | 2% |
| Mathematics | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 13 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 April 2017.
All research outputs
#8,713,411
of 25,806,080 outputs
Outputs from PLoS Computational Biology
#5,683
of 9,043 outputs
Outputs of similar age
#73,743
of 251,086 outputs
Outputs of similar age from PLoS Computational Biology
#45
of 116 outputs
Altmetric has tracked 25,806,080 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,043 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 251,086 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 116 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 55% of its contemporaries.