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A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis

Overview of attention for article published in Cell Division, April 2013
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1 tweeter

Citations

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13 Dimensions

Readers on

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46 Mendeley
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1 CiteULike
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Title
A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis
Published in
Cell Division, April 2013
DOI 10.1186/1747-1028-8-6
Pubmed ID
Abstract

The yeast Schizosaccharomyces pombe is frequently used as a model for studying the cell cycle. The cells are rod-shaped and divide by medial fission. The process of cell division, or cytokinesis, is controlled by a network of signaling proteins called the Septation Initiation Network (SIN); SIN proteins associate with the SPBs during nuclear division (mitosis). Some SIN proteins associate with both SPBs early in mitosis, and then display strongly asymmetric signal intensity at the SPBs in late mitosis, just before cytokinesis. This asymmetry is thought to be important for correct regulation of SIN signaling, and coordination of cytokinesis and mitosis. In order to study the dynamics of organelles or large protein complexes such as the spindle pole body (SPB), which have been labeled with a fluorescent protein tag in living cells, a number of the image analysis problems must be solved; the cell outline must be detected automatically, and the position and signal intensity associated with the structures of interest within the cell must be determined.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

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 Kingdom 2 4%
United States 2 4%
Spain 1 2%
Germany 1 2%
Unknown 40 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 35%
Researcher 11 24%
Student > Master 8 17%
Professor > Associate Professor 3 7%
Lecturer 2 4%
Other 4 9%
Unknown 2 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 37%
Engineering 6 13%
Computer Science 5 11%
Biochemistry, Genetics and Molecular Biology 5 11%
Social Sciences 2 4%
Other 6 13%
Unknown 5 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 April 2013.
All research outputs
#2,926,221
of 6,228,985 outputs
Outputs from Cell Division
#27
of 56 outputs
Outputs of similar age
#48,597
of 97,930 outputs
Outputs of similar age from Cell Division
#1
of 1 outputs
Altmetric has tracked 6,228,985 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 56 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 35th percentile – i.e., 35% 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 97,930 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them