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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrating gene expression and protein-protein interaction network to prioritize cancer-associated genes
|
|---|---|
| Published in |
BMC Bioinformatics, July 2012
|
| DOI | 10.1186/1471-2105-13-182 |
| Pubmed ID | |
| Authors |
Chao Wu, Jun Zhu, Xuegong Zhang |
| Abstract |
To understand the roles they play in complex diseases, genes need to be investigated in the networks they are involved in. Integration of gene expression and network data is a promising approach to prioritize disease-associated genes. Some methods have been developed in this field, but the problem is still far from being solved. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| Netherlands | 2 | 2% |
| United States | 2 | 2% |
| Malaysia | 1 | <1% |
| Italy | 1 | <1% |
| Brazil | 1 | <1% |
| India | 1 | <1% |
| France | 1 | <1% |
| Estonia | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 113 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 35 | 27% |
| Researcher | 26 | 20% |
| Student > Master | 11 | 9% |
| Student > Bachelor | 8 | 6% |
| Professor | 7 | 5% |
| Other | 25 | 20% |
| Unknown | 16 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 38% |
| Biochemistry, Genetics and Molecular Biology | 26 | 20% |
| Computer Science | 22 | 17% |
| Medicine and Dentistry | 4 | 3% |
| Engineering | 3 | 2% |
| Other | 7 | 5% |
| Unknown | 18 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 19 September 2012.
All research outputs
#7,755,290
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#3,083
of 7,400 outputs
Outputs of similar age
#55,527
of 165,760 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 103 outputs
Altmetric has tracked 23,577,654 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 7,400 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 165,760 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.