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 *

318 related articles for article (PubMed ID: 30287886)

  • 1. 'NetShift': a methodology for understanding 'driver microbes' from healthy and disease microbiome datasets.
    Kuntal BK; Chandrakar P; Sadhu S; Mande SS
    ISME J; 2019 Feb; 13(2):442-454. PubMed ID: 30287886
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deeper insight into the structure of the anaerobic digestion microbial community; the biogas microbiome database is expanded with 157 new genomes.
    Treu L; Kougias PG; Campanaro S; Bassani I; Angelidaki I
    Bioresour Technol; 2016 Sep; 216():260-6. PubMed ID: 27243603
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Nonpareil: a redundancy-based approach to assess the level of coverage in metagenomic datasets.
    Rodriguez-R LM; Konstantinidis KT
    Bioinformatics; 2014 Mar; 30(5):629-35. PubMed ID: 24123672
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A powerful microbiome-based association test and a microbial taxa discovery framework for comprehensive association mapping.
    Koh H; Blaser MJ; Li H
    Microbiome; 2017 Apr; 5(1):45. PubMed ID: 28438217
    [TBL] [Abstract][Full Text] [Related]  

  • 5. VITCOMIC2: visualization tool for the phylogenetic composition of microbial communities based on 16S rRNA gene amplicons and metagenomic shotgun sequencing.
    Mori H; Maruyama T; Yano M; Yamada T; Kurokawa K
    BMC Syst Biol; 2018 Mar; 12(Suppl 2):30. PubMed ID: 29560821
    [TBL] [Abstract][Full Text] [Related]  

  • 6. MetagenoNets: comprehensive inference and meta-insights for microbial correlation networks.
    Nagpal S; Singh R; Yadav D; Mande SS
    Nucleic Acids Res; 2020 Jul; 48(W1):W572-W579. PubMed ID: 32338757
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.
    Tandon D; Haque MM; Mande SS
    PLoS One; 2016; 11(4):e0154493. PubMed ID: 27124399
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Vikodak--A Modular Framework for Inferring Functional Potential of Microbial Communities from 16S Metagenomic Datasets.
    Nagpal S; Haque MM; Mande SS
    PLoS One; 2016; 11(2):e0148347. PubMed ID: 26848568
    [TBL] [Abstract][Full Text] [Related]  

  • 9. iVikodak-A Platform and Standard Workflow for Inferring, Analyzing, Comparing, and Visualizing the Functional Potential of Microbial Communities.
    Nagpal S; Haque MM; Singh R; Mande SS
    Front Microbiol; 2018; 9():3336. PubMed ID: 30692979
    [No Abstract]   [Full Text] [Related]  

  • 10. Metagenomics meets time series analysis: unraveling microbial community dynamics.
    Faust K; Lahti L; Gonze D; de Vos WM; Raes J
    Curr Opin Microbiol; 2015 Jun; 25():56-66. PubMed ID: 26005845
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Understanding the microbiome: Emerging biomarkers for exploiting the microbiota for personalized medicine against cancer.
    Rajpoot M; Sharma AK; Sharma A; Gupta GK
    Semin Cancer Biol; 2018 Oct; 52(Pt 1):1-8. PubMed ID: 29425888
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Application of metagenomics in the human gut microbiome.
    Wang WL; Xu SY; Ren ZG; Tao L; Jiang JW; Zheng SS
    World J Gastroenterol; 2015 Jan; 21(3):803-14. PubMed ID: 25624713
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Piphillin: Improved Prediction of Metagenomic Content by Direct Inference from Human Microbiomes.
    Iwai S; Weinmaier T; Schmidt BL; Albertson DG; Poloso NJ; Dabbagh K; DeSantis TZ
    PLoS One; 2016; 11(11):e0166104. PubMed ID: 27820856
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An accurate and fast alignment-free method for profiling microbial communities.
    Pham DT; Gao S; Phan V
    J Bioinform Comput Biol; 2017 Jun; 15(3):1740001. PubMed ID: 28345370
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Impact of DNA extraction, sample dilution, and reagent contamination on 16S rRNA gene sequencing of human feces.
    Velásquez-Mejía EP; de la Cuesta-Zuluaga J; Escobar JS
    Appl Microbiol Biotechnol; 2018 Jan; 102(1):403-411. PubMed ID: 29079861
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Inference of Environmental Factor-Microbe and Microbe-Microbe Associations from Metagenomic Data Using a Hierarchical Bayesian Statistical Model.
    Yang Y; Chen N; Chen T
    Cell Syst; 2017 Jan; 4(1):129-137.e5. PubMed ID: 28125788
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Explaining diversity in metagenomic datasets by phylogenetic-based feature weighting.
    Albanese D; De Filippo C; Cavalieri D; Donati C
    PLoS Comput Biol; 2015 Mar; 11(3):e1004186. PubMed ID: 25815895
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles.
    Shaw GT; Pao YY; Wang D
    BMC Bioinformatics; 2016 Nov; 17(1):488. PubMed ID: 27887570
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 16.