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A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions
BACKGROUND: Non-additive interactions among genes are frequently associated with a number of phenotypes, including known complex diseases such as Alzheimer’s, diabetes, and cardiovascular disease. Detecting interactions requires careful selection of analytical methods, and some machine learning algo...
Autores principales: | Orlenko, Alena, Moore, Jason H. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7847145/ https://www.ncbi.nlm.nih.gov/pubmed/33514397 http://dx.doi.org/10.1186/s13040-021-00243-0 |
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