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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Refining a steroidogenic model: an analysis of RNA-seq datasets from insect prothoracic glands
|
|---|---|
| Published in |
BMC Genomics, July 2018
|
| DOI | 10.1186/s12864-018-4896-2 |
| Pubmed ID | |
| Authors |
Panagiotis Moulos, Alexandros Alexandratos, Ioannis Nellas, Skarlatos G. Dedos |
| Abstract |
The prothoracic gland (PG), the principal steroidogenic organ of insects, has been proposed as a model for steroid hormone biosynthesis and regulation. To validate the robustness of the model, we present an analysis of accumulated transcriptomic data from PGs of two model species, Drosophila melanogaster and Bombyx mori. We identify that the common core components of the model in both species are encoded by nine genes. Five of these are Halloween genes whose expression differs substantially between the PGs of these species. We conclude that the PGs can be a model for steroid hormone synthesis and regulation within the context of mitochondrial cholesterol transport and steroid biosynthesis but beyond these core mechanisms, gene expression in insect PGs is too diverse to fit in a context-specific model and should be analysed within a species-specific framework. |
X Demographics
The data shown below were collected from the profiles of 5 X users 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 | 20% |
| China | 1 | 20% |
| France | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 29% |
| Student > Master | 2 | 12% |
| Researcher | 2 | 12% |
| Professor | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 4 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 41% |
| Biochemistry, Genetics and Molecular Biology | 5 | 29% |
| Chemistry | 1 | 6% |
| Unknown | 4 | 24% |
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 December 2018.
All research outputs
#13,901,936
of 23,577,654 outputs
Outputs from BMC Genomics
#5,121
of 10,777 outputs
Outputs of similar age
#170,839
of 327,984 outputs
Outputs of similar age from BMC Genomics
#86
of 200 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,777 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 49th percentile – i.e., 49% 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 327,984 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 200 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 54% of its contemporaries.