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 *

168 related articles for article (PubMed ID: 32636817)

  • 1. Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples.
    Marizzoni M; Gurry T; Provasi S; Greub G; Lopizzo N; Ribaldi F; Festari C; Mazzelli M; Mombelli E; Salvatore M; Mirabelli P; Franzese M; Soricelli A; Frisoni GB; Cattaneo A
    Front Microbiol; 2020; 11():1262. PubMed ID: 32636817
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [Comparison of gut microbiotal compositional analysis of patients with irritable bowel syndrome through different bioinformatics pipelines].
    Zhu SW; Liu ZJ; Li M; Zhu HQ; Duan LP
    Beijing Da Xue Xue Bao Yi Xue Ban; 2018 Apr; 50(2):231-238. PubMed ID: 29643520
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Taxonomic annotation of 16S rRNA sequences of pig intestinal samples using MG-RAST and QIIME2 generated different microbiota compositions.
    Lima J; Manning T; Rutherford KM; Baima ET; Dewhurst RJ; Walsh P; Roehe R
    J Microbiol Methods; 2021 Jul; 186():106235. PubMed ID: 33974954
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Interpretations of Environmental Microbial Community Studies Are Biased by the Selected 16S rRNA (Gene) Amplicon Sequencing Pipeline.
    Straub D; Blackwell N; Langarica-Fuentes A; Peltzer A; Nahnsen S; Kleindienst S
    Front Microbiol; 2020; 11():550420. PubMed ID: 33193131
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comparing bioinformatic pipelines for microbial 16S rRNA amplicon sequencing.
    Prodan A; Tremaroli V; Brolin H; Zwinderman AH; Nieuwdorp M; Levin E
    PLoS One; 2020; 15(1):e0227434. PubMed ID: 31945086
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of Mothur and QIIME for the Analysis of Rumen Microbiota Composition Based on 16S rRNA Amplicon Sequences.
    López-García A; Pineda-Quiroga C; Atxaerandio R; Pérez A; Hernández I; García-Rodríguez A; González-Recio O
    Front Microbiol; 2018; 9():3010. PubMed ID: 30619117
    [No Abstract]   [Full Text] [Related]  

  • 7. A comparison of sequencing platforms and bioinformatics pipelines for compositional analysis of the gut microbiome.
    Allali I; Arnold JW; Roach J; Cadenas MB; Butz N; Hassan HM; Koci M; Ballou A; Mendoza M; Ali R; Azcarate-Peril MA
    BMC Microbiol; 2017 Sep; 17(1):194. PubMed ID: 28903732
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Primer, Pipelines, Parameters: Issues in 16S rRNA Gene Sequencing.
    Abellan-Schneyder I; Matchado MS; Reitmeier S; Sommer A; Sewald Z; Baumbach J; List M; Neuhaus K
    mSphere; 2021 Feb; 6(1):. PubMed ID: 33627512
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data.
    Odom AR; Faits T; Castro-Nallar E; Crandall KA; Johnson WE
    Sci Rep; 2023 Aug; 13(1):13957. PubMed ID: 37633998
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluating the accuracy of amplicon-based microbiome computational pipelines on simulated human gut microbial communities.
    Golob JL; Margolis E; Hoffman NG; Fredricks DN
    BMC Bioinformatics; 2017 May; 18(1):283. PubMed ID: 28558684
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Microbiome depiction through user-adapted bioinformatic pipelines and parameters.
    Nayman EI; Schwartz BA; Polanco FC; Firek AK; Gumabong AC; Hofstee NJ; Narasimhan G; Cickovski T; Mathee K
    J Med Microbiol; 2023 Oct; 72(10):. PubMed ID: 37823280
    [No Abstract]   [Full Text] [Related]  

  • 12. Enhancing the Resolution of Rumen Microbial Classification from Metatranscriptomic Data Using Kraken and Mothur.
    Neves ALA; Li F; Ghoshal B; McAllister T; Guan LL
    Front Microbiol; 2017; 8():2445. PubMed ID: 29270165
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A framework for assessing 16S rRNA marker-gene survey data analysis methods using mixtures.
    Olson ND; Kumar MS; Li S; Braccia DJ; Hao S; Timp W; Salit ML; Stine OC; Bravo HC
    Microbiome; 2020 Mar; 8(1):35. PubMed ID: 32169095
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fast and Simple Analysis of MiSeq Amplicon Sequencing Data with MetaAmp.
    Dong X; Kleiner M; Sharp CE; Thorson E; Li C; Liu D; Strous M
    Front Microbiol; 2017; 8():1461. PubMed ID: 28824589
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Evaluating Bioinformatic Pipeline Performance for Forensic Microbiome Analysis
    Kaszubinski SF; Pechal JL; Schmidt CJ; Jordan HR; Benbow ME; Meek MH
    J Forensic Sci; 2020 Mar; 65(2):513-525. PubMed ID: 31657871
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multi-amplicon microbiome data analysis pipelines for mixed orientation sequences using QIIME2: Assessing reference database, variable region and pre-processing bias in classification of mock bacterial community samples.
    Maki KA; Wolff B; Varuzza L; Green SJ; Barb JJ
    PLoS One; 2023; 18(1):e0280293. PubMed ID: 36638095
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Tissue-Associated Bacterial Alterations in Rectal Carcinoma Patients Revealed by 16S rRNA Community Profiling.
    Thomas AM; Jesus EC; Lopes A; Aguiar S; Begnami MD; Rocha RM; Carpinetti PA; Camargo AA; Hoffmann C; Freitas HC; Silva IT; Nunes DN; Setubal JC; Dias-Neto E
    Front Cell Infect Microbiol; 2016; 6():179. PubMed ID: 28018861
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Systematic processing of ribosomal RNA gene amplicon sequencing data.
    Tremblay J; Yergeau E
    Gigascience; 2019 Dec; 8(12):. PubMed ID: 31816087
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities.
    O'Sullivan DM; Doyle RM; Temisak S; Redshaw N; Whale AS; Logan G; Huang J; Fischer N; Amos GCA; Preston MD; Marchesi JR; Wagner J; Parkhill J; Motro Y; Denise H; Finn RD; Harris KA; Kay GL; O'Grady J; Ransom-Jones E; Wu H; Laing E; Studholme DJ; Benavente ED; Phelan J; Clark TG; Moran-Gilad J; Huggett JF
    Sci Rep; 2021 May; 11(1):10590. PubMed ID: 34012005
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.