BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

187 related articles for article (PubMed ID: 33552122)

  • 1. A Zero-Inflated Latent Dirichlet Allocation Model for Microbiome Studies.
    Deek RA; Li H
    Front Genet; 2020; 11():602594. PubMed ID: 33552122
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Testing latent class of subjects with structural zeros in negative binomial models with applications to gut microbiome data.
    Ye P; Qiao X; Tang W; Wang C; He H
    Stat Methods Med Res; 2022 Nov; 31(11):2237-2254. PubMed ID: 35899309
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Bayesian variable selection for multivariate zero-inflated models: Application to microbiome count data.
    Lee KH; Coull BA; Moscicki AB; Paster BJ; Starr JR
    Biostatistics; 2020 Jul; 21(3):499-517. PubMed ID: 30590511
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data.
    Xu L; Paterson AD; Turpin W; Xu W
    PLoS One; 2015; 10(7):e0129606. PubMed ID: 26148172
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Testing latent classes in gut microbiome data using generalized Poisson regression models.
    Qiao X; He H; Sun L; Bai S; Ye P
    Stat Med; 2024 Jan; 43(1):102-124. PubMed ID: 37921025
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Modelling of zero-inflation improves inference of metagenomic gene count data.
    Jonsson V; Österlund T; Nerman O; Kristiansson E
    Stat Methods Med Res; 2019 Dec; 28(12):3712-3728. PubMed ID: 30474490
    [TBL] [Abstract][Full Text] [Related]  

  • 7. GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data.
    Chen L; Reeve J; Zhang L; Huang S; Wang X; Chen J
    PeerJ; 2018; 6():e4600. PubMed ID: 29629248
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A GLM-based zero-inflated generalized Poisson factor model for analyzing microbiome data.
    Chi J; Ye J; Zhou Y
    Front Microbiol; 2024; 15():1394204. PubMed ID: 38873138
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A logistic normal multinomial regression model for microbiome compositional data analysis.
    Xia F; Chen J; Fung WK; Li H
    Biometrics; 2013 Dec; 69(4):1053-63. PubMed ID: 24128059
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Microbial Networks in SPRING - Semi-parametric Rank-Based Correlation and Partial Correlation Estimation for Quantitative Microbiome Data.
    Yoon G; Gaynanova I; Müller CL
    Front Genet; 2019; 10():516. PubMed ID: 31244881
    [TBL] [Abstract][Full Text] [Related]  

  • 11. HARMONIES: A Hybrid Approach for Microbiome Networks Inference via Exploiting Sparsity.
    Jiang S; Xiao G; Koh AY; Chen Y; Yao B; Li Q; Zhan X
    Front Genet; 2020; 11():445. PubMed ID: 32582274
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MarZIC: A Marginal Mediation Model for Zero-Inflated Compositional Mediators with Applications to Microbiome Data.
    Wu Q; O'Malley J; Datta S; Gharaibeh RZ; Jobin C; Karagas MR; Coker MO; Hoen AG; Christensen BC; Madan JC; Li Z
    Genes (Basel); 2022 Jun; 13(6):. PubMed ID: 35741811
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros.
    Abegaz F; Abedini D; White F; Guerrieri A; Zancarini A; Dong L; Westerhuis JA; van Eeuwijk F; Bouwmeester H; Smilde AK
    Sci Rep; 2024 May; 14(1):12433. PubMed ID: 38816496
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Bayesian zero-inflated Dirichlet-multinomial regression model for multivariate compositional count data.
    Koslovsky MD
    Biometrics; 2023 Dec; 79(4):3239-3251. PubMed ID: 36896642
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Modelling count data with excessive zeros: the need for class prediction in zero-inflated models and the issue of data generation in choosing between zero-inflated and generic mixture models for dental caries data.
    Gilthorpe MS; Frydenberg M; Cheng Y; Baelum V
    Stat Med; 2009 Dec; 28(28):3539-53. PubMed ID: 19902494
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Bayesian clustering of multiple zero-inflated outcomes.
    Franzolini B; Cremaschi A; van den Boom W; De Iorio M
    Philos Trans A Math Phys Eng Sci; 2023 May; 381(2247):20220145. PubMed ID: 36970823
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Bayesian nonparametric analysis for zero-inflated multivariate count data with application to microbiome study.
    Shuler K; Verbanic S; Chen IA; Lee J
    J R Stat Soc Ser C Appl Stat; 2021 Aug; 70(4):961-979. PubMed ID: 37440868
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Zero-Inflated gaussian mixed models for analyzing longitudinal microbiome data.
    Zhang X; Guo B; Yi N
    PLoS One; 2020; 15(11):e0242073. PubMed ID: 33166356
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.
    Kassahun W; Neyens T; Molenberghs G; Faes C; Verbeke G
    Stat Med; 2014 Nov; 33(25):4402-19. PubMed ID: 24957791
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Zero-inflated generalized Dirichlet multinomial regression model for microbiome compositional data analysis.
    Tang ZZ; Chen G
    Biostatistics; 2019 Oct; 20(4):698-713. PubMed ID: 29939212
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.