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Empirical Bayes conditional independence graphs for regulatory network recovery
Motivation: Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is...
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| Main Authors: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2012
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3400959/ https://ncbi.nlm.nih.gov/pubmed/22685074 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/bts312 |
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