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Mendeley readers
Attention Score in Context
| Title |
Genome-wide matching of genes to cellular roles using guilt-by-association models derived from single sample analysis
|
|---|---|
| Published in |
BMC Research Notes, July 2012
|
| DOI | 10.1186/1756-0500-5-370 |
| Pubmed ID | |
| Authors |
Jeff A Klomp, Kyle A Furge |
| Abstract |
High-throughput methods that ascribe a cellular or physiological function for each gene product are useful to understand the roles of genes that have not been extensively characterized by molecular or genetic approaches. One method to infer gene function is "guilt-by-association", in which the expression pattern of a poorly characterized gene is shown to co-vary with the expression of better-characterized genes. The function of the poorly characterized gene is inferred from the known function(s) of the well-described genes. For example, genes co-expressed with transcripts that vary during the cell cycle, development, environmental stresses, and with oncogenesis have been implicated in those processes. |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 7% |
| Germany | 1 | 3% |
| South Africa | 1 | 3% |
| Unknown | 26 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 27% |
| Student > Master | 6 | 20% |
| Researcher | 5 | 17% |
| Student > Bachelor | 4 | 13% |
| Lecturer > Senior Lecturer | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 4 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 33% |
| Biochemistry, Genetics and Molecular Biology | 7 | 23% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Computer Science | 2 | 7% |
| Other | 1 | 3% |
| Unknown | 6 | 20% |
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 02 May 2016.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Research Notes
#1,240
of 4,262 outputs
Outputs of similar age
#54,592
of 164,417 outputs
Outputs of similar age from BMC Research Notes
#35
of 106 outputs
Altmetric has tracked 22,790,780 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 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 164,417 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 106 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 61% of its contemporaries.