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Learning Causal Biological Networks With the Principle of Mendelian Randomization
Although large amounts of genomic data are available, it remains a challenge to reliably infer causal (i. e., regulatory) relationships among molecular phenotypes (such as gene expression), especially when multiple phenotypes are involved. We extend the interpretation of the Principle of Mendelian r...
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| Publicado no: | Front Genet |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6536645/ https://ncbi.nlm.nih.gov/pubmed/31164902 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2019.00460 |
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