Towards reconstruction of gene networks from expression data by supervised learning

@article{Soinov2002TowardsRO,
  title={Towards reconstruction of gene networks from expression data by supervised learning},
  author={Lev Soinov and Maria Krestyaninova and Alvis Brazma},
  journal={Genome Biology},
  year={2002},
  volume={4},
  pages={R6 - R6}
}
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 question by building decision-tree-related classifiers, which predict gene expression from the expression data of other genes. We present algorithms that work for continuous expression levels and do not require a… CONTINUE READING
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