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Mendeley readers
Attention Score in Context
| Title |
Systematic quantification of gene interactions by phenotypic array analysis
|
|---|---|
| Published in |
Genome Biology, June 2004
|
| DOI | 10.1186/gb-2004-5-7-r49 |
| Pubmed ID | |
| Authors |
John L Hartman, Nicholas P Tippery |
| Abstract |
A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations. From a genome screen for hydroxyurea (HU) chemical-genetic interactions, 298 haploid deletion strains were selected for further analysis. The strength of interactions was quantified using a wide range of HU concentrations affecting reference strain growth. The selectivity of interaction was determined by comparison with drugs targeting other cellular processes. Bio-modules were defined as gene clusters with shared strength and selectivity of interaction profiles. The functions and connectivity of modules involved in processes such as DNA repair, protein secretion and metabolic control were inferred from their respective gene composition. The work provides an example of, and a general experimental framework for, quantitative analysis of gene interaction networks that buffer cell growth. |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 12% |
| Sweden | 2 | 3% |
| United Kingdom | 1 | 1% |
| France | 1 | 1% |
| Unknown | 65 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 27% |
| Researcher | 16 | 21% |
| Professor > Associate Professor | 10 | 13% |
| Professor | 8 | 10% |
| Student > Doctoral Student | 5 | 6% |
| Other | 12 | 15% |
| Unknown | 6 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 51% |
| Biochemistry, Genetics and Molecular Biology | 17 | 22% |
| Medicine and Dentistry | 5 | 6% |
| Engineering | 4 | 5% |
| Immunology and Microbiology | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 7 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 27 August 2014.
All research outputs
#6,753,656
of 25,371,288 outputs
Outputs from Genome Biology
#3,158
of 4,467 outputs
Outputs of similar age
#18,209
of 59,080 outputs
Outputs of similar age from Genome Biology
#7
of 20 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
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 28th percentile – i.e., 28% 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 59,080 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 68% of its contemporaries.
We're also able to compare this research output to 20 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 65% of its contemporaries.