Title |
Mining Pure, Strict Epistatic Interactions from High-Dimensional Datasets: Ameliorating the Curse of Dimensionality
|
---|---|
Published in |
PLOS ONE, October 2012
|
DOI | 10.1371/journal.pone.0046771 |
Pubmed ID | |
Authors |
Xia Jiang, Richard E. Neapolitan |
Abstract |
The interaction between loci to affect phenotype is called epistasis. It is strict epistasis if no proper subset of the interacting loci exhibits a marginal effect. For many diseases, it is likely that unknown epistatic interactions affect disease susceptibility. A difficulty when mining epistatic interactions from high-dimensional datasets concerns the curse of dimensionality. There are too many combinations of SNPs to perform an exhaustive search. A method that could locate strict epistasis without an exhaustive search can be considered the brass ring of methods for analyzing high-dimensional datasets. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Italy | 1 | 50% |
United States | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 5% |
Spain | 1 | 2% |
Unknown | 41 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 36% |
Student > Ph. D. Student | 12 | 27% |
Student > Master | 6 | 14% |
Professor > Associate Professor | 4 | 9% |
Lecturer | 1 | 2% |
Other | 2 | 5% |
Unknown | 3 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 12 | 27% |
Agricultural and Biological Sciences | 9 | 20% |
Medicine and Dentistry | 6 | 14% |
Biochemistry, Genetics and Molecular Biology | 4 | 9% |
Neuroscience | 3 | 7% |
Other | 7 | 16% |
Unknown | 3 | 7% |