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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Segmentation and Quantitative Analysis of Epithelial Tissues.
|
|---|---|
| Chapter number | 13 |
| Book title |
Drosophila
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-6371-3_13 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6369-0, 978-1-4939-6371-3
|
| Authors |
Benoit Aigouy, Daiki Umetsu, Suzanne Eaton, Aigouy, Benoit, Umetsu, Daiki, Eaton, Suzanne |
| Editors |
Christian Dahmann |
| Abstract |
Epithelia are tissues that regulate exchanges with the environment. They are very dynamic and can acquire virtually any shape; at the cellular level, they are composed of cells tightly connected by junctions. Most often epithelia are amenable to live imaging; however, the large number of cells composing an epithelium and the absence of informatics tools dedicated to epithelial analysis largely prevented tissue scale studies. Here we present Tissue Analyzer, a free tool that can be used to segment and analyze epithelial cells and monitor tissue dynamics. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 18% |
| Researcher | 11 | 16% |
| Student > Master | 10 | 15% |
| Student > Bachelor | 8 | 12% |
| Student > Doctoral Student | 4 | 6% |
| Other | 7 | 10% |
| Unknown | 16 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 26 | 38% |
| Agricultural and Biological Sciences | 15 | 22% |
| Physics and Astronomy | 5 | 7% |
| Immunology and Microbiology | 1 | 1% |
| Environmental Science | 1 | 1% |
| Other | 5 | 7% |
| Unknown | 15 | 22% |
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 05 January 2018.
All research outputs
#23,196,437
of 25,837,817 outputs
Outputs from Methods in molecular biology
#11,201
of 14,362 outputs
Outputs of similar age
#346,101
of 402,901 outputs
Outputs of similar age from Methods in molecular biology
#1,072
of 1,467 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,362 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 1st percentile – i.e., 1% 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 402,901 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,467 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.