Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6372124 | Mathematical Biosciences | 2013 | 9 Pages |
Abstract
This review focuses on the class of autoregressive models using time course data for inferring gene regulatory networks. The central themes of sparsity, stability and causality are discussed as well as the ability to integrate prior knowledge for successful use of these models for the learning task at hand.
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Agricultural and Biological Sciences (General)
Authors
George Michailidis, Florence d'Alché-Buc,