Structural learning of Gaussian graphical models from microarray data with p larger than n
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 conse...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Bologna
2008-06-01
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| Series: | Statistica |
| Online Access: | http://rivista-statistica.unibo.it/article/view/1212 |