| Title |
Functional tissue units and their primary tissue motifs in multi-scale physiology
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2013
|
| DOI | 10.1186/2041-1480-4-22 |
| Pubmed ID | |
| Authors |
Bernard de Bono, Pierre Grenon, Richard Baldock, Peter Hunter |
| Abstract |
Histology information management relies on complex knowledge derived from morphological tissue analyses. These approaches have not significantly facilitated the general integration of tissue- and molecular-level knowledge across the board in support of a systematic classification of tissue function, as well as the coherent multi-scale study of physiology. Our work aims to support directly these integrative goals. |
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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Mexico | 1 | 2% |
| Portugal | 1 | 2% |
| Unknown | 51 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 20% |
| Student > Master | 7 | 13% |
| Professor | 6 | 11% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Bachelor | 5 | 9% |
| Other | 10 | 19% |
| Unknown | 9 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 20% |
| Engineering | 9 | 17% |
| Biochemistry, Genetics and Molecular Biology | 6 | 11% |
| Computer Science | 6 | 11% |
| Medicine and Dentistry | 5 | 9% |
| Other | 5 | 9% |
| Unknown | 12 | 22% |
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 29 March 2021.
All research outputs
#16,721,208
of 25,371,288 outputs
Outputs from Journal of Biomedical Semantics
#234
of 368 outputs
Outputs of similar age
#134,940
of 222,681 outputs
Outputs of similar age from Journal of Biomedical Semantics
#10
of 16 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 35th percentile – i.e., 35% 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 222,681 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.