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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrating experimental and literature protein-protein interaction data for protein complex prediction
|
|---|---|
| Published in |
BMC Genomics, January 2015
|
| DOI | 10.1186/1471-2164-16-s2-s4 |
| Pubmed ID | |
| Authors |
Yijia Zhang, Hongfei Lin, Zhihao Yang, Jian Wang |
| Abstract |
Accurate determination of protein complexes is crucial for understanding cellular organization and function. High-throughput experimental techniques have generated a large amount of protein-protein interaction (PPI) data, allowing prediction of protein complexes from PPI networks. However, the high-throughput data often includes false positives and false negatives, making accurate prediction of protein complexes difficult. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Bangladesh | 1 | 5% |
| Unknown | 20 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 19% |
| Researcher | 3 | 14% |
| Student > Bachelor | 3 | 14% |
| Professor > Associate Professor | 3 | 14% |
| Student > Master | 2 | 10% |
| Other | 5 | 24% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 33% |
| Engineering | 3 | 14% |
| Agricultural and Biological Sciences | 2 | 10% |
| Psychology | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 5 | 24% |
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 25 February 2015.
All research outputs
#20,263,155
of 22,793,427 outputs
Outputs from BMC Genomics
#9,273
of 10,648 outputs
Outputs of similar age
#295,587
of 351,785 outputs
Outputs of similar age from BMC Genomics
#248
of 276 outputs
Altmetric has tracked 22,793,427 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,648 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% 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 351,785 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 276 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.