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Cited by in F6Publishing
For: Jiang S, Xiao G, Koh AY, Kim J, Li Q, Zhan X. A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data. Biostatistics 2021;22:522-40. [PMID: 31844880 DOI: 10.1093/biostatistics/kxz050] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
Number Citing Articles
1 Chan JSK, Choy STB, Makov U, Shamir A, Shapovalov V. Variable Selection Algorithm for a Mixture of Poisson Regression for Handling Overdispersion in Claims Frequency Modeling Using Telematics Car Driving Data. Risks 2022;10:83. [DOI: 10.3390/risks10040083] [Reference Citation Analysis]
2 Liu T, Xu P, Du Y, Lu H, Zhao H, Wang T. MZINBVA: variational approximation for multilevel zero-inflated negative-binomial models for association analysis in microbiome surveys. Brief Bioinform 2021:bbab443. [PMID: 34718406 DOI: 10.1093/bib/bbab443] [Reference Citation Analysis]
3 Wilson CM, Ospina OE, Townsend MK, Nguyen J, Moran Segura C, Schildkraut JM, Tworoger SS, Peres LC, Fridley BL. Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data. Cancers (Basel) 2021;13:3031. [PMID: 34204319 DOI: 10.3390/cancers13123031] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
4 Rong R, Jiang S, Xu L, Xiao G, Xie Y, Liu DJ, Li Q, Zhan X. MB-GAN: Microbiome Simulation via Generative Adversarial Network. Gigascience 2021;10:giab005. [PMID: 33543271 DOI: 10.1093/gigascience/giab005] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]