Inferring multiple graphical structures

  title={Inferring multiple graphical structures},
  author={Julien Chiquet and Yves Grandvalet and Christophe Ambroise},
  journal={Statistics and Computing},
Abstract: Gaussian Graphical Models provide a convenient framework for representing dependencies between variables. Recently, this tool has received a high interest for the discovery of biological networks. The literature focuses on the case where a single network is inferred from a set of measurements, but, as wetlab data is typically scarce, several assays, where the experimental conditions affect interactions, are usually merged to infer a single network. In this paper, we propose two… CONTINUE READING
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