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Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs
Construction of regulatory networks using cross-sectional expression profiling of genes is desired, but challenging. The Directed Acyclic Graph (DAG) provides a general framework to infer causal effects from observational data. However, most existing DAG methods assume that all nodes follow the same...
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| Publicat a: | Front Genet |
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| Autors principals: | , , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Frontiers Media S.A.
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7038820/ https://ncbi.nlm.nih.gov/pubmed/32127796 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2020.00008 |
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