These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 31510709)

  • 1. Learning a mixture of microbial networks using minorization-maximization.
    Tavakoli S; Yooseph S
    Bioinformatics; 2019 Jul; 35(14):i23-i30. PubMed ID: 31510709
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Variational Approximation-Based Model Selection for Microbial Network Inference.
    Yooseph S; Tavakoli S
    J Comput Biol; 2022 Jul; 29(7):724-737. PubMed ID: 35549398
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MDiNE: a model to estimate differential co-occurrence networks in microbiome studies.
    McGregor K; Labbe A; Greenwood CMT
    Bioinformatics; 2020 Mar; 36(6):1840-1847. PubMed ID: 31697315
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CACONET: a novel classification framework for microbial correlation networks.
    Xu Y; Nash K; Acharjee A; Gkoutos GV
    Bioinformatics; 2022 Mar; 38(6):1639-1647. PubMed ID: 34983063
    [TBL] [Abstract][Full Text] [Related]  

  • 5. NetCoMi: network construction and comparison for microbiome data in R.
    Peschel S; Müller CL; von Mutius E; Boulesteix AL; Depner M
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33264391
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Sparse and compositionally robust inference of microbial ecological networks.
    Kurtz ZD; Müller CL; Miraldi ER; Littman DR; Blaser MJ; Bonneau RA
    PLoS Comput Biol; 2015 May; 11(5):e1004226. PubMed ID: 25950956
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Direct interaction network inference for compositional data via codaloss.
    Chen L; He S; Zhai Y; Deng M
    J Bioinform Comput Biol; 2020 Dec; 18(6):2050037. PubMed ID: 33106076
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation.
    Kishore D; Birzu G; Hu Z; DeLisi C; Korolev KS; Segrè D
    mSystems; 2023 Aug; 8(4):e0096122. PubMed ID: 37338270
    [TBL] [Abstract][Full Text] [Related]  

  • 9. FastSpar: rapid and scalable correlation estimation for compositional data.
    Watts SC; Ritchie SC; Inouye M; Holt KE
    Bioinformatics; 2019 Mar; 35(6):1064-1066. PubMed ID: 30169561
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Inference of microbial covariation networks using copula models with mixture margins.
    Deek RA; Li H
    Bioinformatics; 2023 Jul; 39(7):. PubMed ID: 37379127
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Compositional data network analysis via lasso penalized D-trace loss.
    Yuan H; He S; Deng M
    Bioinformatics; 2019 Sep; 35(18):3404-3411. PubMed ID: 31220226
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A zero inflated log-normal model for inference of sparse microbial association networks.
    Prost V; Gazut S; Brüls T
    PLoS Comput Biol; 2021 Jun; 17(6):e1009089. PubMed ID: 34143768
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A novel normalization and differential abundance test framework for microbiome data.
    Ma Y; Luo Y; Jiang H
    Bioinformatics; 2020 Jul; 36(13):3959-3965. PubMed ID: 32311021
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Umibato: estimation of time-varying microbial interaction using continuous-time regression hidden Markov model.
    Hosoda S; Fukunaga T; Hamada M
    Bioinformatics; 2021 Jul; 37(Suppl_1):i16-i24. PubMed ID: 34252954
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Estimation of sparse directed acyclic graphs for multivariate counts data.
    Han SW; Zhong H
    Biometrics; 2016 Sep; 72(3):791-803. PubMed ID: 26849781
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting microbiomes through a deep latent space.
    García-Jiménez B; Muñoz J; Cabello S; Medina J; Wilkinson MD
    Bioinformatics; 2021 Jun; 37(10):1444-1451. PubMed ID: 33289510
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Poisson hurdle model-based method for clustering microbiome features.
    Qiao Z; Barnes E; Tringe S; Schachtman DP; Liu P
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36469352
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Transformation and differential abundance analysis of microbiome data incorporating phylogeny.
    Zhou C; Zhao H; Wang T
    Bioinformatics; 2021 Dec; 37(24):4652-4660. PubMed ID: 34302462
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MIMOSA2: a metabolic network-based tool for inferring mechanism-supported relationships in microbiome-metabolome data.
    Noecker C; Eng A; Muller E; Borenstein E
    Bioinformatics; 2022 Mar; 38(6):1615-1623. PubMed ID: 34999748
    [TBL] [Abstract][Full Text] [Related]  

  • 20. coda4microbiome: compositional data analysis for microbiome cross-sectional and longitudinal studies.
    Calle ML; Pujolassos M; Susin A
    BMC Bioinformatics; 2023 Mar; 24(1):82. PubMed ID: 36879227
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.