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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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
#14,146,599
of 22,668,244 outputs
Outputs from BMC Research Notes
#1,946
of 4,249 outputs
Outputs of similar age
#98,137
of 166,794 outputs
Outputs of similar age from BMC Research Notes
#41
of 87 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,249 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 50% 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 166,794 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.