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Reverse Engineering of the Spindle Assembly Checkpoint

Overview of attention for article published in PLOS ONE, August 2009
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Title
Reverse Engineering of the Spindle Assembly Checkpoint
Published in
PLOS ONE, August 2009
DOI 10.1371/journal.pone.0006495
Pubmed ID
Authors

Andreas Doncic, Eshel Ben-Jacob, Shmuel Einav, Naama Barkai

Abstract

The Spindle Assembly Checkpoint (SAC) is an intracellular mechanism that ensures proper chromosome segregation. By inhibiting Cdc20, a co-factor of the Anaphase Promoting Complex (APC), the checkpoint arrests the cell cycle until all chromosomes are properly attached to the mitotic spindle. Inhibition of Cdc20 is mediated by a conserved network of interacting proteins. The individual functions of these proteins are well characterized, but understanding of their integrated function is still rudimentary. We here describe our attempts to reverse-engineer the SAC network based on gene deletion phenotypes. We begun by formulating a general model of the SAC which enables us to predict the rate of chromosomal missegregation for any putative set of interactions between the SAC proteins. Next the missegregation rates of seven yeast strains are measured in response to the deletion of one or two checkpoint proteins. Finally, we searched for the set of interactions that correctly predicted the observed missegregation rates of all deletion mutants. Remarkably, although based on only seven phenotypes, the consistent network we obtained successfully reproduces many of the known properties of the SAC. Further insights provided by our analysis are discussed.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
United Kingdom 2 4%
Germany 1 2%
India 1 2%
Spain 1 2%
Estonia 1 2%
Unknown 38 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 43%
Student > Ph. D. Student 13 28%
Professor > Associate Professor 4 9%
Student > Master 3 7%
Professor 2 4%
Other 3 7%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 67%
Biochemistry, Genetics and Molecular Biology 8 17%
Philosophy 1 2%
Business, Management and Accounting 1 2%
Physics and Astronomy 1 2%
Other 0 0%
Unknown 4 9%
Attention Score in Context

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 16 July 2023.
All research outputs
#7,454,298
of 22,789,076 outputs
Outputs from PLOS ONE
#88,765
of 194,533 outputs
Outputs of similar age
#37,200
of 110,943 outputs
Outputs of similar age from PLOS ONE
#250
of 503 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,533 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 49th percentile – i.e., 49% 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 110,943 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 503 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.