Bayesian nonlinear model selection for gene regulatory networks

DOI10.1111/biom.12309zbMath1419.62419OpenAlexW2123895078WikidataQ42584887 ScholiaQ42584887MaRDI QIDQ2803473

Yang Ni, Veerabhadran Baladandayuthapani, Francesco C. Stingo

Publication date: 4 May 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4575256

zbMATH Keywords

directed acyclic graphhierarchical modelMCMCP-splinesgene regulatory networkmodel and functional selection

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (8)

TGCnA: temporal gene coexpression network analysis using a low-rank plus sparse framework ⋮ Reciprocal graphical models for integrative gene regulatory network analysis ⋮ Bayesian graphical models for modern biological applications ⋮ Gaussian graphical modeling for spectrometric data analysis ⋮ Model selection and local geometry ⋮ Inference of gene regulatory networks using Bayesian nonparametric regression and topology information ⋮ Bayesian Approaches for Large Biological Networks ⋮ Bayesian Graphical Regression

Uses Software

• gss
• SemiPar
• hgam

Cites Work

• Unnamed Item
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• Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs
• Detecting Novel Associations in Large Data Sets
• A Bayesian graphical modeling approach to microRNA regulatory network inference
• Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
• Inferring metabolic networks using the Bayesian adaptive graphical Lasso with informative priors
• High-dimensional additive modeling
• Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Inference from iterative simulation using multiple sequences
• Objective Bayesian Search of Gaussian Directed Acyclic Graphical Models for Ordered Variables with Non‐Local Priors
• Inferring the time-invariant topology of a nonlinear sparse gene regulatory network using fully Bayesian spline autoregression
• Semiparametric Regression
• Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models
• Learning Sparse Causal Gaussian Networks With Experimental Intervention: Regularization and Coordinate Descent
• Bayesian Inference of Multiple Gaussian Graphical Models

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