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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiaegene function
|
|---|---|
| Published in |
Genome Biology, June 2008
|
| DOI | 10.1186/gb-2008-9-s1-s7 |
| Pubmed ID | |
| Authors |
Weidong Tian, Lan V Zhang, Murat Taşan, Francis D Gibbons, Oliver D King, Julie Park, Zeba Wunderlich, J Michael Cherry, Frederick P Roth |
| Abstract |
Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 4% |
| United States | 3 | 3% |
| Canada | 2 | 2% |
| Korea, Republic of | 1 | <1% |
| Slovenia | 1 | <1% |
| Germany | 1 | <1% |
| Spain | 1 | <1% |
| Belgium | 1 | <1% |
| Unknown | 96 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 33 | 30% |
| Student > Ph. D. Student | 31 | 28% |
| Student > Bachelor | 9 | 8% |
| Professor | 7 | 6% |
| Student > Master | 6 | 5% |
| Other | 13 | 12% |
| Unknown | 11 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 47 | 43% |
| Biochemistry, Genetics and Molecular Biology | 18 | 16% |
| Computer Science | 15 | 14% |
| Medicine and Dentistry | 8 | 7% |
| Engineering | 4 | 4% |
| Other | 7 | 6% |
| Unknown | 11 | 10% |
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 04 April 2012.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from Genome Biology
#4,269
of 4,467 outputs
Outputs of similar age
#89,013
of 96,206 outputs
Outputs of similar age from Genome Biology
#38
of 43 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. 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 96,206 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.