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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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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
Authors

Daniel Schmitter, Paulina Wachowicz, Daniel Sage, Anastasia Chasapi, Ioannis Xenarios, Viesturs Simanis, Michael Unser

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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 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 44 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 30%
Researcher 12 24%
Student > Master 8 16%
Professor > Associate Professor 3 6%
Student > Bachelor 2 4%
Other 6 12%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 32%
Engineering 7 14%
Biochemistry, Genetics and Molecular Biology 5 10%
Computer Science 5 10%
Psychology 3 6%
Other 7 14%
Unknown 7 14%
Attention Score in Context

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
#18,337,420
of 22,708,120 outputs
Outputs from Cell Division
#91
of 131 outputs
Outputs of similar age
#145,559
of 193,472 outputs
Outputs of similar age from Cell Division
#2
of 2 outputs
Altmetric has tracked 22,708,120 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 131 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 9th percentile – i.e., 9% 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 193,472 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.