A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n

@article{Castelo2006ARP,
  title={A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n},
  author={Robert Castelo and Alberto Roverato},
  journal={Journal of Machine Learning Research},
  year={2006},
  volume={6},
  pages={2621-2650}
}
Learning of large-scale networks of interactions from microarray data is an important and challenging problem in bioinformatics. A widely used approach is to assume that the available data constitute a random sample from a multivariate distribution belonging to a Gaussian graphical model. As a consequence, the prime objects of inference are full-order partial correlations which are partial correlations between two variables given the remaining ones. In the context of microarray data the number… CONTINUE READING

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