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Mendeley readers
Attention Score in Context
| Title |
ProMEX: a mass spectral reference database for proteins and protein phosphorylation sites
|
|---|---|
| Published in |
BMC Bioinformatics, June 2007
|
| DOI | 10.1186/1471-2105-8-216 |
| Pubmed ID | |
| Authors |
Jan Hummel, Michaela Niemann, Stefanie Wienkoop, Waltraud Schulze, Dirk Steinhauser, Joachim Selbig, Dirk Walther, Wolfram Weckwerth |
| Abstract |
In the last decade, techniques were established for the large scale genome-wide analysis of proteins, RNA, and metabolites, and database solutions have been developed to manage the generated data sets. The Golm Metabolome Database for metabolite data (GMD) represents one such effort to make these data broadly available and to interconnect the different molecular levels of a biological system 1. As data interpretation in the light of already existing data becomes increasingly important, these initiatives are an essential part of current and future systems biology. |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| Hong Kong | 1 | 1% |
| Brazil | 1 | 1% |
| Hungary | 1 | 1% |
| Finland | 1 | 1% |
| Mexico | 1 | 1% |
| Belgium | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 82 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 27 | 30% |
| Student > Ph. D. Student | 19 | 21% |
| Professor > Associate Professor | 7 | 8% |
| Student > Master | 7 | 8% |
| Professor | 5 | 5% |
| Other | 17 | 19% |
| Unknown | 9 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 53% |
| Chemistry | 10 | 11% |
| Biochemistry, Genetics and Molecular Biology | 9 | 10% |
| Computer Science | 8 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Other | 5 | 5% |
| Unknown | 10 | 11% |
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 03 February 2024.
All research outputs
#7,451,584
of 22,780,967 outputs
Outputs from BMC Bioinformatics
#3,020
of 7,277 outputs
Outputs of similar age
#24,602
of 68,598 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 48 outputs
Altmetric has tracked 22,780,967 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 7,277 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 68,598 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 48 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.