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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An Improvement of Shotgun Proteomics Analysis by Adding Next-Generation Sequencing Transcriptome Data in Orange
|
|---|---|
| Published in |
PLOS ONE, June 2012
|
| DOI | 10.1371/journal.pone.0039494 |
| Pubmed ID | |
| Authors |
Jiaping Song, Renjie Sun, Dazhi Li, Fengji Tan, Xin Li, Pingping Jiang, Xinjie Huang, Liang Lin, Ziniu Deng, Yong Zhang |
| Abstract |
Shotgun proteomics data analysis usually relies on database search. Because commonly employed protein sequence databases of most species do not contain sufficient protein information, the application of shotgun proteomics to the research of protein sequence profile remains a big challenge, especially to the species whose genome has not been sequenced yet. |
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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| India | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 42 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 31% |
| Researcher | 9 | 20% |
| Professor > Associate Professor | 5 | 11% |
| Student > Doctoral Student | 3 | 7% |
| Student > Bachelor | 3 | 7% |
| Other | 10 | 22% |
| Unknown | 1 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 44% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Computer Science | 6 | 13% |
| Engineering | 4 | 9% |
| Chemistry | 2 | 4% |
| Other | 4 | 9% |
| Unknown | 1 | 2% |
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 02 July 2012.
All research outputs
#18,309,495
of 22,669,724 outputs
Outputs from PLOS ONE
#153,778
of 193,515 outputs
Outputs of similar age
#126,274
of 164,182 outputs
Outputs of similar age from PLOS ONE
#3,128
of 3,987 outputs
Altmetric has tracked 22,669,724 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,515 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 10th percentile – i.e., 10% 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 164,182 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,987 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.