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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of genes associated with multiple cancers via integrative analysis
|
|---|---|
| Published in |
BMC Genomics, November 2009
|
| DOI | 10.1186/1471-2164-10-535 |
| Pubmed ID | |
| Authors |
Shuangge Ma, Jian Huang, Meena S Moran |
| Abstract |
Advancement in gene profiling techniques makes it possible to measure expressions of thousands of genes and identify genes associated with development and progression of cancer. The identified cancer-associated genes can be used for diagnosis, prognosis prediction, and treatment selection. Most existing cancer microarray studies have been focusing on the identification of genes associated with a specific type of cancer. Recent biomedical studies suggest that different cancers may share common susceptibility genes. A comprehensive description of the associations between genes and cancers requires identification of not only multiple genes associated with a specific type of cancer but also genes associated with multiple cancers. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | 50% |
| Poland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 12% |
| France | 1 | 4% |
| Canada | 1 | 4% |
| Unknown | 20 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 36% |
| Researcher | 7 | 28% |
| Student > Master | 3 | 12% |
| Student > Postgraduate | 2 | 8% |
| Other | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 48% |
| Computer Science | 3 | 12% |
| Medicine and Dentistry | 3 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 8% |
| Mathematics | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 2 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 15 December 2012.
All research outputs
#8,527,291
of 25,374,647 outputs
Outputs from BMC Genomics
#3,904
of 11,244 outputs
Outputs of similar age
#51,714
of 178,607 outputs
Outputs of similar age from BMC Genomics
#27
of 64 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 65% 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 178,607 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 64 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 57% of its contemporaries.