Generalized Hierarchical Markov Models for the Discovery of Length‐Constrained Sequence Features from Genome Tiling Arrays

DOI10.1111/J.1541-0420.2007.00760.XzbMath1146.62087OpenAlexW2112022804WikidataQ48385552 ScholiaQ48385552MaRDI QIDQ5434910

Mayetri Gupta

Publication date: 14 January 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://cdr.lib.unc.edu/downloads/k0698j20m

zbMATH Keywords

data augmentationBayesian hierarchical modelgene regulationchromatinnucleosome

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Monte Carlo methods (65C05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Biochemistry, molecular biology (92C40)

Uses Software

• BioProspector

Cites Work

• Inference from iterative simulation using multiple sequences
• Biological Sequence Analysis
• Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes
• Discovery of Conserved Sequence Patterns Using a Stochastic Dictionary Model
• A note on direct and inverse binomial sampling

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