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Mendeley readers
Attention Score in Context
| Title |
CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources
|
|---|---|
| Published in |
BMC Microbiology, March 2010
|
| DOI | 10.1186/1471-2180-10-88 |
| Pubmed ID | |
| Authors |
David Goudenège, Stéphane Avner, Céline Lucchetti-Miganeh, Frédérique Barloy-Hubler |
| Abstract |
The functions of proteins are strongly related to their localization in cell compartments (for example the cytoplasm or membranes) but the experimental determination of the sub-cellular localization of proteomes is laborious and expensive. A fast and low-cost alternative approach is in silico prediction, based on features of the protein primary sequences. However, biologists are confronted with a very large number of computational tools that use different methods that address various localization features with diverse specificities and sensitivities. As a result, exploiting these computer resources to predict protein localization accurately involves querying all tools and comparing every prediction output; this is a painstaking task. Therefore, we developed a comprehensive database, called CoBaltDB, that gathers all prediction outputs concerning complete prokaryotic proteomes. |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 7% |
| Sweden | 1 | 2% |
| France | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 39 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 22% |
| Researcher | 10 | 22% |
| Student > Master | 5 | 11% |
| Student > Bachelor | 4 | 9% |
| Professor > Associate Professor | 3 | 7% |
| Other | 9 | 20% |
| Unknown | 4 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 49% |
| Computer Science | 5 | 11% |
| Engineering | 4 | 9% |
| Biochemistry, Genetics and Molecular Biology | 3 | 7% |
| Business, Management and Accounting | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 8 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 31 December 2016.
All research outputs
#7,453,350
of 22,786,087 outputs
Outputs from BMC Microbiology
#857
of 3,186 outputs
Outputs of similar age
#34,460
of 94,529 outputs
Outputs of similar age from BMC Microbiology
#5
of 13 outputs
Altmetric has tracked 22,786,087 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,186 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 65% 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 94,529 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 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.