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Updated: Jan 4, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

Microbiome data science.

Sudarshan A Shetty¹, Leo Lahti

¹Laboratory of Microbiology, Wageningen University and Research, Wageningen, The Netherlands.

Journal of Biosciences

|November 14, 2019

Summary

This summary is machine-generated.

Open data science enhances research transparency and efficiency. Microbiome data science applies these practices, fostering collaboration and creating educational resources for this rapidly growing field.

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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

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Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

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Published on: May 2, 2018

Area of Science:

Microbiome Bioinformatics
Open Data Science
Computational Biology

Background:

Open data science principles are increasingly adopted across research disciplines.
Digitalization facilitates resource sharing, collaboration, and outreach in scientific research.
Microbiome bioinformatics is a dynamic field poised to benefit from open science advancements.

Purpose of the Study:

To define and explore the emerging field of microbiome data science.
To outline the integration of open data science best practices within microbiome research.
To provide a community developer's perspective on the current state and future trajectory of microbiome data science.

Main Methods:

Review of open data science best practices.
Application of these practices to microbiome bioinformatics challenges.
Community-driven development and ecosystem building.

Main Results:

Microbiome data science integrates experimental data with open analysis and reproducible tutorials.
An ecosystem is forming that combines data, processing, analysis, and education.
The field benefits from increased data availability and online collaboration opportunities.

Conclusions:

Microbiome data science enhances research transparency, efficiency, and educational outreach.
The development of a robust microbiome data science ecosystem is crucial for future progress.
Continued community involvement and open practices will drive innovation in microbiome research.