Doubly stochastic continuous-time hidden Markov approach for analyzing genome tiling arrays

DOI10.1214/09-AOAS248zbMath1196.62141arXiv0910.2090OpenAlexW3105098933MaRDI QIDQ985036

Jun S. Liu, X. Shirley Liu, W. Evan Johnson

Publication date: 20 July 2010

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

Full work available at URL: https://arxiv.org/abs/0910.2090

zbMATH Keywords

hidden Markov modelMarkov chain Monte CarloBayesian hierarchical modelforward-backward algorithmcontinuous-space Markov chainexpectation conditional maximizationtiling microarray

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Biochemistry, molecular biology (92C40) Numerical analysis or methods applied to Markov chains (65C40) Genetics and epigenetics (92D10)

Related Items (2)

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Uses Software

• xMAN

Cites Work

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• Doubly stochastic continuous-time hidden Markov approach for analyzing genome tiling arrays
• Bioinformatics and computational biology solutions using R and Bioconductor.
• Maximum likelihood estimation via the ECM algorithm: A general framework
• A Flexible and Powerful Bayesian Hierarchical Model for ChIP-Chip Experiments
• Mixture Modeling for Genome‐Wide Localization of Transcription Factors
• ChIP‐chip: Data, Model, and Analysis

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