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Towards reconstruction of gene networks from expression data by supervised learning
BACKGROUND: Microarray experiments are generating datasets that can help in reconstructing gene networks. One of the most important problems in network reconstruction is finding, for each gene in the network, which genes can affect it and how. We use a supervised learning approach to address this qu...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2003
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC151290/ https://www.ncbi.nlm.nih.gov/pubmed/12540298 |