↓ Skip to main content

A method for improved clustering and classification of microscopy images using quantitative co-localization coefficients

Overview of attention for article published in BMC Research Notes, June 2012
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 tweeter
linkedin
1 LinkedIn user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
18 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A method for improved clustering and classification of microscopy images using quantitative co-localization coefficients
Published in
BMC Research Notes, June 2012
DOI 10.1186/1756-0500-5-281
Pubmed ID
Authors

Vasanth R Singan, Kenan Handzic, Kathleen M Curran, Jeremy C Simpson

Abstract

The localization of proteins to specific subcellular structures in eukaryotic cells provides important information with respect to their function. Fluorescence microscopy approaches to determine localization distribution have proved to be an essential tool in the characterization of unknown proteins, and are now particularly pertinent as a result of the wide availability of fluorescently-tagged constructs and antibodies. However, there are currently very few image analysis options able to effectively discriminate proteins with apparently similar distributions in cells, despite this information being important for protein characterization.

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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 22%
Professor > Associate Professor 3 17%
Student > Master 3 17%
Student > Bachelor 2 11%
Student > Ph. D. Student 2 11%
Other 4 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 39%
Biochemistry, Genetics and Molecular Biology 5 28%
Engineering 2 11%
Psychology 1 6%
Medicine and Dentistry 1 6%
Other 1 6%
Unknown 1 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 20 June 2012.
All research outputs
#7,225,905
of 12,519,627 outputs
Outputs from BMC Research Notes
#1,189
of 2,804 outputs
Outputs of similar age
#57,819
of 118,633 outputs
Outputs of similar age from BMC Research Notes
#9
of 19 outputs
Altmetric has tracked 12,519,627 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,804 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 54% 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 118,633 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.