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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case
|
|---|---|
| Published in |
BMC Bioinformatics, August 2011
|
| DOI | 10.1186/1471-2105-12-351 |
| Pubmed ID | |
| Authors |
Thomas A Russ, Cartic Ramakrishnan, Eduard H Hovy, Mihail Bota, Gully APC Burns |
| Abstract |
We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. |
X Demographics
The data shown below were collected from the profiles of 4 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 States | 1 | 25% |
| Sweden | 1 | 25% |
| Egypt | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 11% |
| Korea, Republic of | 1 | 1% |
| Switzerland | 1 | 1% |
| Unknown | 62 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 24% |
| Professor > Associate Professor | 10 | 14% |
| Student > Ph. D. Student | 8 | 11% |
| Professor | 7 | 10% |
| Student > Bachelor | 6 | 8% |
| Other | 19 | 26% |
| Unknown | 5 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 23 | 32% |
| Agricultural and Biological Sciences | 19 | 26% |
| Medicine and Dentistry | 7 | 10% |
| Engineering | 5 | 7% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Other | 6 | 8% |
| Unknown | 8 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 10 November 2017.
All research outputs
#7,394,948
of 23,877,717 outputs
Outputs from BMC Bioinformatics
#2,785
of 7,483 outputs
Outputs of similar age
#40,610
of 126,150 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 76 outputs
Altmetric has tracked 23,877,717 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,483 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 gotten more attention than average, scoring higher than 60% 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 126,150 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 76 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 55% of its contemporaries.