A Bayesian graphical modeling approach to microRNA regulatory network inference

DOI10.1214/10-AOAS360zbMath1220.62142arXiv1101.1377WikidataQ37089017 ScholiaQ37089017MaRDI QIDQ542971

Yian A. Chen, Marianne Barrier, Philip E. Mirkes, Francesco C. Stingo, Marina Vannucci

Publication date: 20 June 2011

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1101.1377

zbMATH Keywords

data integrationgraphical modelsBayesian variable selectionmiRNA regulatory network

Mathematics Subject Classification ID

Multivariate analysis (62H99) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Applications of graph theory (05C90) Search theory (90B40) Biochemistry, molecular biology (92C40)

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Cites Work

• A hidden spatial-temporal Markov random field model for network-based analysis of time course gene expression data
• Bayesian Variable Selection in Multinomial Probit Models to Identify Molecular Signatures of Disease Stage
• Some matrix-variate distribution theory: Notational considerations and a Bayesian application
• Multivariate Bayesian Variable Selection and Prediction
• Probabilistic Networks and Expert Systems
• Detecting differential gene expression with a semiparametric hierarchical mixture method
• A stochastic partitioning method to associate high-dimensional responses and covariates

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