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A Bayesian hierarchical model for analyzing methylated RNA immunoprecipitation sequencing data.

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第一作者： Minzhe,Zhang

第一单位： Quantitative Biomedical Research Center, Department of Clinical Sciences, U.T. Southwestern Medical Center, Dallas, TX 75390, USA.

作者： Minzhe,Zhang ^[1] ; Qiwei,Li ^[1] ; Yang,Xie ^[2]

作者单位： Quantitative Biomedical Research Center, Department of Clinical Sciences, U.T. Southwestern Medical Center, Dallas, TX 75390, USA. ^[1] Quantitative Biomedical Research Center, Department of Clinical Sciences, U.T. Southwestern Medical Center, Dallas, TX 75390, USA.;Department of Bioinformatics, U.T. Southwestern Medical Center, Dallas, TX 75390, USA.;Simmons Comprehensive Cancer Center, U.T. Southwestern Medical Center, Dallas, TX 75390, USA. ^[2]

关键词 Bayesian inference MeRIP-seq data RNA epigenomics hidden Markov model zero-inflated negative binomial

DOI 10.1007/s40484-018-0149-2

PMID 33833899

发布时间 2022-04-21

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Quantitative biology (Beijing, China)

2018年6卷3期

275-286页

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Quantitative biology (Beijing, China)

2018年6卷3期

275-286页

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A Bayesian hierarchical model for analyzing methylated RNA immunoprecipitation sequencing data.

Quantitative biology (Beijing, China)

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A Bayesian hierarchical model for analyzing methylated RNA immunoprecipitation sequencing data.

Quantitative biology (Beijing, China)

相似文献

同项目论文

Quantitative biology (Beijing, China)

相关期刊

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