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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of the effectiveness of simple nuclei-segmentation methods on Caenorhabditis elegans embryogenesis images
|
|---|---|
| Published in |
BMC Bioinformatics, October 2013
|
| DOI | 10.1186/1471-2105-14-295 |
| Pubmed ID | |
| Authors |
Yusuke Azuma, Shuichi Onami |
| Abstract |
For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems. Thus, it is useful to evaluate the ability of simple methods to segment images with various degrees of crowded nuclei. |
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 % |
|---|---|---|
| United Kingdom | 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 6% |
| Germany | 1 | 3% |
| Unknown | 31 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 29% |
| Researcher | 8 | 24% |
| Student > Bachelor | 5 | 15% |
| Professor > Associate Professor | 3 | 9% |
| Student > Master | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 5 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 38% |
| Computer Science | 7 | 21% |
| Biochemistry, Genetics and Molecular Biology | 3 | 9% |
| Engineering | 3 | 9% |
| Neuroscience | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 6 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 15 June 2014.
All research outputs
#4,102,471
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#1,558
of 7,387 outputs
Outputs of similar age
#37,444
of 209,169 outputs
Outputs of similar age from BMC Bioinformatics
#25
of 98 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,387 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 done well, scoring higher than 78% 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 209,169 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 82% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.