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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Adaptable data management for systems biology investigations
|
|---|---|
| Published in |
BMC Bioinformatics, March 2009
|
| DOI | 10.1186/1471-2105-10-79 |
| Pubmed ID | |
| Authors |
John Boyle, Hector Rovira, Chris Cavnor, David Burdick, Sarah Killcoyne, Ilya Shmulevich |
| Abstract |
Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 4% |
| United Kingdom | 3 | 3% |
| Sweden | 3 | 3% |
| Portugal | 2 | 2% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Australia | 1 | <1% |
| Hong Kong | 1 | <1% |
| Singapore | 1 | <1% |
| Other | 3 | 3% |
| Unknown | 92 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 31% |
| Student > Ph. D. Student | 20 | 18% |
| Student > Master | 14 | 13% |
| Other | 10 | 9% |
| Professor | 7 | 6% |
| Other | 18 | 16% |
| Unknown | 8 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 50 | 45% |
| Computer Science | 16 | 14% |
| Biochemistry, Genetics and Molecular Biology | 13 | 12% |
| Medicine and Dentistry | 10 | 9% |
| Immunology and Microbiology | 2 | 2% |
| Other | 11 | 10% |
| Unknown | 10 | 9% |
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 11 May 2015.
All research outputs
#14,142,336
of 22,661,413 outputs
Outputs from BMC Bioinformatics
#4,707
of 7,241 outputs
Outputs of similar age
#77,532
of 93,399 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 49 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,241 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 93,399 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.