Towards reconstruction of gene networks from expression data by supervised learning

AUTOR(ES)

Soinov, Lev A

FONTE

BioMed Central

RESUMO

One of the most important problems in gene network reconstruction is finding, for each gene in the network, which genes can affect it. A supervised learning approach was used to address this question in budding yeast by building decision-tree-related classifiers, which predict gene expression from the expression data of other genes.

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