BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

186 related articles for article (PubMed ID: 27635321)

  • 1. A heritability-based comparison of methods used to cluster 16S rRNA gene sequences into operational taxonomic units.
    Jackson MA; Bell JT; Spector TD; Steves CJ
    PeerJ; 2016; 4():e2341. PubMed ID: 27635321
    [TBL] [Abstract][Full Text] [Related]  

  • 2. De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units.
    Westcott SL; Schloss PD
    PeerJ; 2015; 3():e1487. PubMed ID: 26664811
    [TBL] [Abstract][Full Text] [Related]  

  • 3. OptiFit: an Improved Method for Fitting Amplicon Sequences to Existing OTUs.
    Sovacool KL; Westcott SL; Mumphrey MB; Dotson GA; Schloss PD
    mSphere; 2022 Feb; 7(1):e0091621. PubMed ID: 35107341
    [TBL] [Abstract][Full Text] [Related]  

  • 4. OptiClust, an Improved Method for Assigning Amplicon-Based Sequence Data to Operational Taxonomic Units.
    Westcott SL; Schloss PD
    mSphere; 2017; 2(2):. PubMed ID: 28289728
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.
    He Y; Caporaso JG; Jiang XT; Sheng HF; Huse SM; Rideout JR; Edgar RC; Kopylova E; Walters WA; Knight R; Zhou HW
    Microbiome; 2015; 3():20. PubMed ID: 25995836
    [TBL] [Abstract][Full Text] [Related]  

  • 6. An independent evaluation in a CRC patient cohort of microbiome 16S rRNA sequence analysis methods: OTU clustering, DADA2, and Deblur.
    Liu G; Li T; Zhu X; Zhang X; Wang J
    Front Microbiol; 2023; 14():1178744. PubMed ID: 37560524
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Machine learning classification by fitting amplicon sequences to existing OTUs.
    Armour CR; Sovacool KL; Close WL; Topçuoğlu BD; Wiens J; Schloss PD
    mSphere; 2023 Oct; 8(5):e0033623. PubMed ID: 37615431
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Assessing and improving methods used in operational taxonomic unit-based approaches for 16S rRNA gene sequence analysis.
    Schloss PD; Westcott SL
    Appl Environ Microbiol; 2011 May; 77(10):3219-26. PubMed ID: 21421784
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved OTU-picking using long-read 16S rRNA gene amplicon sequencing and generic hierarchical clustering.
    Franzén O; Hu J; Bao X; Itzkowitz SH; Peter I; Bashir A
    Microbiome; 2015 Oct; 3():43. PubMed ID: 26434730
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A comparison of methods for clustering 16S rRNA sequences into OTUs.
    Chen W; Zhang CK; Cheng Y; Zhang S; Zhao H
    PLoS One; 2013; 8(8):e70837. PubMed ID: 23967117
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Distribution-based clustering: using ecology to refine the operational taxonomic unit.
    Preheim SP; Perrotta AR; Martin-Platero AM; Gupta A; Alm EJ
    Appl Environ Microbiol; 2013 Nov; 79(21):6593-603. PubMed ID: 23974136
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Reconciliation between operational taxonomic units and species boundaries.
    Mysara M; Vandamme P; Props R; Kerckhof FM; Leys N; Boon N; Raes J; Monsieurs P
    FEMS Microbiol Ecol; 2017 Apr; 93(4):. PubMed ID: 28334218
    [TBL] [Abstract][Full Text] [Related]  

  • 13. DBH: A de Bruijn graph-based heuristic method for clustering large-scale 16S rRNA sequences into OTUs.
    Wei ZG; Zhang SW
    J Theor Biol; 2017 Jul; 425():80-87. PubMed ID: 28454900
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DMSC: A Dynamic Multi-Seeds Method for Clustering 16S rRNA Sequences Into OTUs.
    Wei ZG; Zhang SW
    Front Microbiol; 2019; 10():428. PubMed ID: 30915052
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A De Novo Robust Clustering Approach for Amplicon-Based Sequence Data.
    Bazin A; Debroas D; Mephu Nguifo E
    J Comput Biol; 2019 Jun; 26(6):618-624. PubMed ID: 30517025
    [No Abstract]   [Full Text] [Related]  

  • 16. bioOTU: An Improved Method for Simultaneous Taxonomic Assignments and Operational Taxonomic Units Clustering of 16s rRNA Gene Sequences.
    Chen SY; Deng F; Huang Y; Jia X; Liu YP; Lai SJ
    J Comput Biol; 2016 Apr; 23(4):229-38. PubMed ID: 26950196
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Nitrogen Cycling Microbial Diversity and Operational Taxonomic Unit Clustering: When to Prioritize Accuracy Over Speed.
    Egenriether S; Sanford R; Yang WH; Kent AD
    Front Microbiol; 2022; 13():730340. PubMed ID: 35722279
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of Methods for Picking the Operational Taxonomic Units From Amplicon Sequences.
    Wei ZG; Zhang XD; Cao M; Liu F; Qian Y; Zhang SW
    Front Microbiol; 2021; 12():644012. PubMed ID: 33841367
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods.
    Schloss PD
    mSystems; 2016; 1(2):. PubMed ID: 27832214
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Ecological consistency of SSU rRNA-based operational taxonomic units at a global scale.
    Schmidt TS; Matias Rodrigues JF; von Mering C
    PLoS Comput Biol; 2014 Apr; 10(4):e1003594. PubMed ID: 24763141
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.