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Learning gene regulatory networks from only positive and unlabeled data

BACKGROUND: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled as a binary classification problem for each pair of genes. A statistical classifier is trained to recognize the relation...

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Detalles Bibliográficos
Autores principales: Cerulo, Luigi, Elkan, Charles, Ceccarelli, Michele
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2887423/
https://www.ncbi.nlm.nih.gov/pubmed/20444264
http://dx.doi.org/10.1186/1471-2105-11-228

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