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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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| 出版年: | Front Genet |
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| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2019
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| 主題: | |
| オンライン・アクセス: | 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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