| Title |
eMouseAtlas informatics: embryo atlas and gene expression database
|
|---|---|
| Published in |
Mammalian Genome, August 2015
|
| DOI | 10.1007/s00335-015-9596-5 |
| Pubmed ID | |
| Authors |
Chris Armit, Lorna Richardson, Bill Hill, Yiya Yang, Richard A. Baldock |
| Abstract |
A significant proportion of developmental biology data is presented in the form of images at morphologically diverse stages of development. The curation of these datasets presents different challenges to that of sequence/text-based data. Towards this end, the eMouseAtlas project created a digital atlas of mouse embryo development as a means of understanding developmental anatomy and exploring the relationship between genes and development in a spatial context. Using the morphological staging system pioneered by Karl Theiler, the project has generated 3D models of post-implantation mouse development and used them as a spatial framework for the delineation of anatomical components and for archiving in situ gene expression data in the EMAGE database. This has allowed us to develop a unique online resource for mouse developmental biology. We describe here the underlying structure of the resource, as well as some of the tools that have been developed to allow users to mine the curated image data. These tools include our IIP3D/X3DOM viewer that allows 3D visualisation of anatomy and/or gene expression in the context of a web browser, and the eHistology resource that extends this functionality to allow visualisation of high-resolution cellular level images of histology sections. Furthermore, we review some of the informatics aspects of eMouseAtlas to provide a deeper insight into the use of the atlas and gene expression database. |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 27% |
| Professor | 3 | 20% |
| Student > Ph. D. Student | 2 | 13% |
| Lecturer | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 40% |
| Agricultural and Biological Sciences | 4 | 27% |
| Computer Science | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Neuroscience | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 2 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 24 November 2016.
All research outputs
#5,717,604
of 22,860,626 outputs
Outputs from Mammalian Genome
#258
of 1,126 outputs
Outputs of similar age
#66,516
of 266,283 outputs
Outputs of similar age from Mammalian Genome
#6
of 14 outputs
Altmetric has tracked 22,860,626 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,126 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 77% 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 266,283 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 75% of its contemporaries.
We're also able to compare this research output to 14 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 57% of its contemporaries.