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DREAM3: Network Inference Using Dynamic Context Likelihood of Relatedness and the Inferelator
BACKGROUND: Many current works aiming to learn regulatory networks from systems biology data must balance model complexity with respect to data availability and quality. Methods that learn regulatory associations based on unit-less metrics, such as Mutual Information, are attractive in that they sca...
| Autores principales: | , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2010
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2842436/ https://www.ncbi.nlm.nih.gov/pubmed/20339551 http://dx.doi.org/10.1371/journal.pone.0009803 |