GBDR: a Bayesian model for precise prediction of pathogenic microorganisms using 16S rRNA gene sequences
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2164
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
GBDR: a Bayesian model for precise prediction of pathogenic microorganisms using 16S rRNA gene sequences ; volume:22 ; number:1 ; day:16 ; month:3 ; year:2022 ; pages:1-15 ; date:6.2021
BMC genomics ; 22, Heft 1 (16.3.2022), 1-15, 6.2021
- Urheber
-
Huang, Yu-An
Huang, Zhi-An
Li, Jian-Qiang
You, Zhu-Hong
Wang, Lei
Yi, Hai-Cheng
Yu, Chang-Qing
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s12864-022-08423-w
- URN
-
urn:nbn:de:101:1-2022060820103414156361
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:32 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Huang, Yu-An
- Huang, Zhi-An
- Li, Jian-Qiang
- You, Zhu-Hong
- Wang, Lei
- Yi, Hai-Cheng
- Yu, Chang-Qing
- SpringerLink (Online service)
Ähnliche Objekte (12)
Bacterial genotyping by 16S rRNA mass cataloging
Analysis of 16S rRNA environmental sequences using MEGAN
Differential richness inference for 16S rRNA marker gene surveys
Comparison of 16S rRNA gene sequences of genus Methanobrevibacter
Deep learning for predicting 16S rRNA gene copy number
Pathogenic microorganisms and viruses in groundwater
A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues
16S rRNA sequencing of samples from universal stool bank donors
metaSPARSim: a 16S rRNA gene sequencing count data simulator
Head lice as vectors of pathogenic microorganisms
Ultrafast and accurate 16S rRNA microbial community analysis using Kraken 2
16S rRNA metagenome clustering and diversity estimation using locality sensitive hashing
Bacterial genotyping by 16S rRNA mass cataloging
Analysis of 16S rRNA environmental sequences using MEGAN
Differential richness inference for 16S rRNA marker gene surveys
Comparison of 16S rRNA gene sequences of genus Methanobrevibacter
Deep learning for predicting 16S rRNA gene copy number
Pathogenic microorganisms and viruses in groundwater
A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues
16S rRNA sequencing of samples from universal stool bank donors
metaSPARSim: a 16S rRNA gene sequencing count data simulator
Head lice as vectors of pathogenic microorganisms
Ultrafast and accurate 16S rRNA microbial community analysis using Kraken 2
16S rRNA metagenome clustering and diversity estimation using locality sensitive hashing
Bacterial genotyping by 16S rRNA mass cataloging
Analysis of 16S rRNA environmental sequences using MEGAN
Differential richness inference for 16S rRNA marker gene surveys
Comparison of 16S rRNA gene sequences of genus Methanobrevibacter
Deep learning for predicting 16S rRNA gene copy number
Pathogenic microorganisms and viruses in groundwater
A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues
16S rRNA sequencing of samples from universal stool bank donors
metaSPARSim: a 16S rRNA gene sequencing count data simulator
Head lice as vectors of pathogenic microorganisms
Ultrafast and accurate 16S rRNA microbial community analysis using Kraken 2