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Gradient Directed Regularization For Sparse Gaussian Concentration Graphs, With Applications To Inference Of Genetic Networks, Hongzhe Li, Jiang Gui
Gradient Directed Regularization For Sparse Gaussian Concentration Graphs, With Applications To Inference Of Genetic Networks, Hongzhe Li, Jiang Gui
UPenn Biostatistics Working Papers
Large-scale microarray gene expression data provide the possibility of constructing genetic networks or biological pathways. Gaussian graphical models have been suggested to provide an effective method for constructing such genetic networks. However, most of the available methods for constructing Gaussian graphs do not account for the sparsity of the networks and are computationally more demanding or infeasible, especially in the settings of high-dimension and low sample size. We introduce a threshold gradient descent regularization procedure for estimating the sparse precision matrix in the setting of Gaussian graphical models and demonstrate its application to identifying genetic networks. Such a procedure is …