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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
13
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pubmed:dateCreated |
2011-6-20
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pubmed:abstractText |
In recent years, numerous genome-wide association studies have been conducted to identify genetic makeup that explains phenotypic differences observed in human population. Analytical tests on single loci are readily available and embedded in common genome analysis software toolset. The search for significant epistasis (gene-gene interactions) still poses as a computational challenge for modern day computing systems, due to the large number of hypotheses that have to be tested.
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Jul
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pubmed:issn |
1367-4811
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:day |
1
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pubmed:volume |
27
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
i214-21
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pubmed:meshHeading |
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pubmed:year |
2011
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pubmed:articleTitle |
Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs.
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pubmed:affiliation |
Statistical Genetics, Max Planck Institute of Psychiatry, Munich, Germany. tony@mpipsykl.mpg.de
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
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