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Mendeley readers
Attention Score in Context
| Title |
HybGFS: a hybrid method for genome-fingerprint scanning
|
|---|---|
| Published in |
BMC Bioinformatics, October 2006
|
| DOI | 10.1186/1471-2105-7-479 |
| Pubmed ID | |
| Authors |
Kosaku Shinoda, Nozomu Yachie, Takeshi Masuda, Naoyuki Sugiyama, Masahiro Sugimoto, Tomoyoshi Soga, Masaru Tomita |
| Abstract |
Protein identification based on mass spectrometry (MS) has previously been performed using peptide mass fingerprinting (PMF) or tandem MS (MS/MS) database searching. However, these methods cannot identify proteins that are not already listed in existing databases. Moreover, the alternative approach of de novo sequencing requires costly equipment and the interpretation of complex MS/MS spectra. Thus, there is a need for novel high-throughput protein-identification methods that are independent of existing predefined protein databases. |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 8% |
| France | 1 | 8% |
| Unknown | 10 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 33% |
| Student > Ph. D. Student | 2 | 17% |
| Other | 1 | 8% |
| Student > Master | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 58% |
| Chemistry | 2 | 17% |
| Computer Science | 2 | 17% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
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 22 September 2013.
All research outputs
#7,453,827
of 22,787,797 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#23,957
of 68,736 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 53 outputs
Altmetric has tracked 22,787,797 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 7,279 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 68,736 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 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.