Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
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[1] M. Frydenberg,et al. Decomposition of maximum likelihood in mixed graphical interaction models , 1989 .
[2] D. Edwards. Introduction to graphical modelling , 1995 .
[3] Padhraic Smyth,et al. Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series , 2004, UAI.
[4] C. N. Liu,et al. Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.
[5] Nathan Srebro,et al. Maximum likelihood bounded tree-width Markov networks , 2001, Artif. Intell..
[6] Michael I. Jordan. Graphical Models , 1998 .
[7] N. Wermuth. Model Search among Multiplicative Models , 1976 .
[8] N. Wermuth,et al. Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative , 1989 .
[9] Robert M. Blumenthal,et al. Activation from a Distance: Roles of Lrp and Integration Host Factor in Transcriptional Activation ofgltBDF , 2001, Journal of bacteriology.
[10] D. Madigan,et al. On the Markov Equivalence of Chain Graphs, Undirected Graphs, and Acyclic Digraphs , 1997 .
[11] Marina Meila,et al. An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High-Dimensional Sparse Data , 1999, ICML.
[12] Stan Matwin,et al. A formal approach to using data distributions for building causal polytree structures , 2004, Inf. Sci..
[13] J. Kruskal. On the shortest spanning subtree of a graph and the traveling salesman problem , 1956 .
[14] Carsten O. Daub,et al. The mutual information: Detecting and evaluating dependencies between variables , 2002, ECCB.
[15] Gordon K Smyth,et al. Statistical Applications in Genetics and Molecular Biology Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2011 .
[16] Pedro Larrañaga,et al. A Guide to the Literature on Inferring Genetic Networks by Probabilistic Graphical Models , 2005, Data Analysis and Visualization in Genomics and Proteomics.
[17] S. Shen-Orr,et al. Network motifs: simple building blocks of complex networks. , 2002, Science.
[18] N. Camp,et al. Graphical modeling of the joint distribution of alleles at associated loci. , 2004, American journal of human genetics.
[19] Nir Friedman,et al. Inferring Cellular Networks Using Probabilistic Graphical Models , 2004, Science.
[20] E.S. Manolakos,et al. A Graphical Model Formulation of the DNA Base-Calling Problem , 2005, 2005 IEEE Workshop on Machine Learning for Signal Processing.
[21] David Maxwell Chickering,et al. Learning Bayesian Networks is NP-Complete , 2016, AISTATS.
[22] G. W. Hatfield,et al. Global Gene Expression Profiling in Escherichia coli K12 , 2003, Journal of Biological Chemistry.
[23] Andrew W. Moore,et al. Dependency trees in sub-linear time and bounded memory , 2006, The VLDB Journal.
[24] Robert Castelo,et al. Reverse Engineering Molecular Regulatory Networks from Microarray Data with qp-Graphs , 2009, J. Comput. Biol..
[25] David Maxwell Chickering,et al. Learning Bayesian Networks: The Combination of Knowledge and Statistical Data , 1994, Machine Learning.
[26] G. W. Hatfield,et al. Global gene expression profiling in Escherichia coli K12. The effects of integration host factor. , 2000, The Journal of biological chemistry.
[27] Nathan Srebro,et al. Methods and Experiments With Bounded Tree-width Markov Networks , 2004 .
[28] Terry J. Wagner,et al. Consistency of an estimate of tree-dependent probability distributions (Corresp.) , 1973, IEEE Trans. Inf. Theory.
[29] P. Hall,et al. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[30] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[31] H. Akaike. A new look at the statistical model identification , 1974 .
[32] Chris Wiggins,et al. ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context , 2004, BMC Bioinformatics.
[33] Concettina Guerra,et al. A review on models and algorithms for motif discovery in protein-protein interaction networks. , 2008, Briefings in functional genomics & proteomics.
[34] Doug Fisher,et al. Learning from Data: Artificial Intelligence and Statistics V , 1996 .
[35] BMC Bioinformatics , 2005 .
[36] Martin J. Wainwright,et al. Embedded trees: estimation of Gaussian Processes on graphs with cycles , 2004, IEEE Transactions on Signal Processing.
[37] Michael I. Jordan,et al. Learning with Mixtures of Trees , 2001, J. Mach. Learn. Res..
[38] Judea Pearl,et al. Equivalence and Synthesis of Causal Models , 1990, UAI.
[39] Peter Bühlmann,et al. Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm , 2007, J. Mach. Learn. Res..
[40] Christian L. Barrett,et al. Genome-scale reconstruction of the Lrp regulatory network in Escherichia coli , 2008, Proceedings of the National Academy of Sciences.
[41] Tom Burr,et al. Causation, Prediction, and Search , 2003, Technometrics.
[42] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[43] Joaquín Dopazo,et al. Data Analysis and Visualization in Genomics and Proteomics , 2005 .
[44] David R. Anderson,et al. Multimodel Inference , 2004 .
[45] Pierre Baldi,et al. Global Gene Expression Profiling in Escherichia coliK12 , 2002, The Journal of Biological Chemistry.
[46] Michael I. Jordan,et al. Thin Junction Trees , 2001, NIPS.