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Mendeley readers
Attention Score in Context
| Title |
Information-theoretic gene-gene and gene-environment interaction analysis of quantitative traits
|
|---|---|
| Published in |
BMC Genomics, November 2009
|
| DOI | 10.1186/1471-2164-10-509 |
| Pubmed ID | |
| Authors |
Pritam Chanda, Lara Sucheston, Song Liu, Aidong Zhang, Murali Ramanathan |
| Abstract |
The purpose of this research was to develop a novel information theoretic method and an efficient algorithm for analyzing the gene-gene (GGI) and gene-environmental interactions (GEI) associated with quantitative traits (QT). The method is built on two information-theoretic metrics, the k-way interaction information (KWII) and phenotype-associated information (PAI). The PAI is a novel information theoretic metric that is obtained from the total information correlation (TCI) information theoretic metric by removing the contributions for inter-variable dependencies (resulting from factors such as linkage disequilibrium and common sources of environmental pollutants). |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 46 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 29% |
| Student > Master | 9 | 19% |
| Student > Ph. D. Student | 7 | 15% |
| Professor | 5 | 10% |
| Other | 3 | 6% |
| Other | 6 | 13% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 44% |
| Biochemistry, Genetics and Molecular Biology | 6 | 13% |
| Computer Science | 4 | 8% |
| Medicine and Dentistry | 4 | 8% |
| Mathematics | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 5 | 10% |
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 September 2019.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Genomics
#3,597
of 10,647 outputs
Outputs of similar age
#34,129
of 94,474 outputs
Outputs of similar age from BMC Genomics
#12
of 35 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 10,647 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% 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 94,474 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.