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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The EnzymeTracker: an open-source laboratory information management system for sample tracking
|
|---|---|
| Published in |
BMC Bioinformatics, January 2012
|
| DOI | 10.1186/1471-2105-13-15 |
| Pubmed ID | |
| Authors |
Thomas Triplet, Gregory Butler |
| Abstract |
In many laboratories, researchers store experimental data on their own workstation using spreadsheets. However, this approach poses a number of problems, ranging from sharing issues to inefficient data-mining. Standard spreadsheets are also error-prone, as data do not undergo any validation process. To overcome spreadsheets inherent limitations, a number of proprietary systems have been developed, which laboratories need to pay expensive license fees for. Those costs are usually prohibitive for most laboratories and prevent scientists from benefiting from more sophisticated data management systems. |
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 % |
|---|---|---|
| Germany | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 2% |
| Canada | 2 | 2% |
| Germany | 1 | 1% |
| Bangladesh | 1 | 1% |
| South Africa | 1 | 1% |
| Australia | 1 | 1% |
| Denmark | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 74 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 27% |
| Student > Master | 9 | 11% |
| Student > Bachelor | 7 | 8% |
| Student > Ph. D. Student | 6 | 7% |
| Student > Postgraduate | 6 | 7% |
| Other | 17 | 20% |
| Unknown | 16 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 24% |
| Medicine and Dentistry | 13 | 15% |
| Computer Science | 11 | 13% |
| Biochemistry, Genetics and Molecular Biology | 6 | 7% |
| Engineering | 4 | 5% |
| Other | 14 | 17% |
| Unknown | 16 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 28 January 2012.
All research outputs
#18,171,876
of 23,340,595 outputs
Outputs from BMC Bioinformatics
#6,063
of 7,388 outputs
Outputs of similar age
#194,283
of 248,961 outputs
Outputs of similar age from BMC Bioinformatics
#59
of 70 outputs
Altmetric has tracked 23,340,595 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 12th percentile – i.e., 12% 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 248,961 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.