Inference of genetic regulatory networks with regulatory hubs using vector autoregressions and automatic relevance determination with model selections

DOI10.1515/SAGMB-2020-0054zbMath1496.92048OpenAlexW4200325741MaRDI QIDQ2170542

Chi-Kan Chen

Publication date: 6 September 2022

Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/sagmb-2020-0054

zbMATH Keywords

model selectiongene expression time seriesARDGRN inferenceregulatory hubVAR1

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10) Systems biology, networks (92C42)

Cites Work

• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Weighted-LASSO for structured network inference from time course data
• Autoregressive models for gene regulatory network inference: sparsity, stability and causality issues
• 10.1162/15324430152748236
• Bayesian Networks in R
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• Regularization and Variable Selection Via the Elastic Net
• Reconstructing Gene Regulatory Networks with Bayesian Networks by Combining Expression Data with Multiple Sources of Prior Knowledge
• A General Framework for Weighted Gene Co-Expression Network Analysis
• Unnamed Item

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