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Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs.
TLDR
We propose an efficient penalized likelihood method for estimation of the adjacency matrix of directed acyclic graphs, when variables inherit a natural ordering. Expand
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Discovering graphical Granger causality using the truncating lasso penalty
TLDR
We propose a novel penalization method, called truncating lasso, for estimation of causal relationships from time-course gene expression data and show that the proposed method can consistently discover causal relationships in the large p, small n setting. Expand
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Selection and estimation for mixed graphical models.
We consider the problem of estimating the parameters in a pairwise graphical model in which the distribution of each node, conditioned on the others, may have a different exponential family form. WeExpand
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The Multivariate Hawkes Process in High Dimensions: Beyond Mutual Excitation
The Hawkes process is a class of point processes whose future depends on their own history. Previous theoretical work on the Hawkes process is limited to a special case in which a past event can onlyExpand
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Neural Granger Causality for Nonlinear Time Series
While most classical approaches to Granger causality detection assume linear dynamics, many interactions in applied domains, like neuroscience and genomics, are inherently nonlinear. In these cases,Expand
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Metabolomic profiling reveals potential markers and bioprocesses altered in bladder cancer progression.
Although alterations in xenobiotic metabolism are considered causal in the development of bladder cancer, the precise mechanisms involved are poorly understood. In this study, we used high-throughputExpand
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Analysis of Gene Sets Based on the Underlying Regulatory Network
TLDR
In this paper, we propose a model-based approach for testing the significance of biological pathways using the underlying gene network and studied graph theoretic properties of the model. Expand
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The cluster graphical lasso for improved estimation of Gaussian graphical models
TLDR
The task of estimating a Gaussian graphical model in the high-dimensional setting is considered. Expand
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Inhibition of the hexosamine biosynthetic pathway promotes castration-resistant prostate cancer
The precise molecular alterations driving castration-resistant prostate cancer (CRPC) are not clearly understood. Using a novel network-based integrative approach, here, we show distinct alterationsExpand
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Network granger causality with inherent grouping structure
TLDR
In this work, we aim to learn a network structure from temporal panel data, employing the framework of Granger causal models under the assumptions of sparsity of its edges and inherent grouping structure among its nodes. Expand
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