Bayesian hidden Markov models to identify RNA–protein interaction sites in PAR‐CLIP

DOI10.1111/biom.12147zbMath1419.62486OpenAlexW2110428330WikidataQ40815627 ScholiaQ40815627MaRDI QIDQ5170214

Guanghua Xiao, Tao Wang, Jonghyun Yun

Publication date: 22 July 2014

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4061157

zbMATH Keywords

Markov chain Monte Carlonext generation sequencing datanon-homogeneous hidden Markov modelbeta geometricPAR-CLIPRNA binding protein

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Protein sequences, DNA sequences (92D20)

Uses Software

• DEseq
• HPeak
• CLIPZ
• ChIPDiff

Cites Work

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• Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
• Detecting differential gene expression with a semiparametric hierarchical mixture method
• A Bayesian Hidden Markov Model for Motif Discovery Through Joint Modeling of Genomic Sequence and ChIP‐Chip Data

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