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Accurate, precise modeling of cell proliferation kinetics from time-lapse imaging and automated image analysis of agar yeast culture arrays

Overview of attention for article published in BMC Systems Biology, January 2007
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog

Citations

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46 Dimensions

Readers on

mendeley
60 Mendeley
connotea
1 Connotea
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Title
Accurate, precise modeling of cell proliferation kinetics from time-lapse imaging and automated image analysis of agar yeast culture arrays
Published in
BMC Systems Biology, January 2007
DOI 10.1186/1752-0509-1-3
Pubmed ID
Authors

Najaf A Shah, Richard J Laws, Bradley Wardman, Lue Ping Zhao, John L Hartman

Abstract

Genome-wide mutant strain collections have increased demand for high throughput cellular phenotyping (HTCP). For example, investigators use HTCP to investigate interactions between gene deletion mutations and additional chemical or genetic perturbations by assessing differences in cell proliferation among the collection of 5000 S. cerevisiae gene deletion strains. Such studies have thus far been predominantly qualitative, using agar cell arrays to subjectively score growth differences. Quantitative systems level analysis of gene interactions would be enabled by more precise HTCP methods, such as kinetic analysis of cell proliferation in liquid culture by optical density. However, requirements for processing liquid cultures make them relatively cumbersome and low throughput compared to agar. To improve HTCP performance and advance capabilities for quantifying interactions, YeastXtract software was developed for automated analysis of cell array images.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
United Kingdom 2 3%
Germany 1 2%
Finland 1 2%
Sweden 1 2%
Lithuania 1 2%
Poland 1 2%
Unknown 50 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 27%
Researcher 15 25%
Student > Bachelor 5 8%
Professor 5 8%
Professor > Associate Professor 4 7%
Other 9 15%
Unknown 6 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 43%
Computer Science 8 13%
Biochemistry, Genetics and Molecular Biology 6 10%
Engineering 5 8%
Mathematics 2 3%
Other 6 10%
Unknown 7 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 27 August 2014.
All research outputs
#5,873,643
of 22,761,738 outputs
Outputs from BMC Systems Biology
#196
of 1,142 outputs
Outputs of similar age
#33,462
of 157,830 outputs
Outputs of similar age from BMC Systems Biology
#4
of 7 outputs
Altmetric has tracked 22,761,738 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 82% 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 157,830 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 78% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.