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Related Concept Videos

Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
Introduction to the Human Microbiota01:22

Introduction to the Human Microbiota

Microorganisms colonize various regions of the human body, including the mouth, nasal passages, throat, stomach, intestines, urogenital tract, and skin. The total number of microbial cells is estimated to range from 10¹³ to 10¹⁴—comparable to, or exceeding, the number of human somatic cells. This host–microbiome relationship has led to the conceptualization of humans as supraorganisms, wherein microbial communities perform vital roles in development, immunity, and disease...
Genomic DNA in Prokaryotes00:46

Genomic DNA in Prokaryotes

The genome of most prokaryotic organisms consists of double-stranded DNA organized into one circular chromosome in a region of cytoplasm called the nucleoid. The chromosome is tightly wound, or supercoiled, for efficient storage. Prokaryotes also contain other circular pieces of DNA called plasmids. These plasmids are smaller than the chromosome and often carry genes that confer adaptive functions, such as antibiotic resistance.
Genomic Diversity in Bacteria
Although bacterial genomes are much...
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
Evolution of Microbial Genome01:08

Evolution of Microbial Genome

Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.

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Related Experiment Video

Updated: Jun 15, 2026

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere
09:55

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

Published on: May 2, 2018

A primer on metagenomics.

John C Wooley1, Adam Godzik, Iddo Friedberg

  • 1Community Cyberinfrastructure for Marine Microbial Ecology Research and Analysis, California Institute for Telecommunications and Information Technology, University of California San Diego, La Jolla, California, United States of America.

Plos Computational Biology
|March 3, 2010
PubMed
Summary
This summary is machine-generated.

Metagenomics allows studying uncultured microbes using advanced sequencing. Bioinformatics tools are crucial for analyzing the vast, complex data generated from microbial communities.

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Related Experiment Videos

Last Updated: Jun 15, 2026

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere
09:55

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Published on: May 2, 2018

Metagenomic Analysis of Silage
08:43

Metagenomic Analysis of Silage

Published on: January 13, 2017

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
11:23

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Metagenomics studies uncultured microorganisms directly from their environments.
  • Advances in sequencing technology have led to a surge in available genomic data.
  • Analyzing complex microbial communities presents significant bioinformatic challenges.

Purpose of the Study:

  • To provide an introduction to the computational requirements of metagenomics.
  • To review recent progress in bioinformatics methods for metagenomic data analysis.
  • To highlight software tools and their utility in metagenomic research.

Main Methods:

  • Discusses computational challenges in sequence assembly and annotation for heterogeneous microbial communities.
  • Reviews the development of new bioinformatic algorithms and approaches.
  • Identifies and evaluates software solutions for metagenomic data processing.

Main Results:

  • Highlights the increasing demands on bioinformatics due to voluminous, noisy, and partial sequence data.
  • Presents a review of current computational methods and recent advancements.
  • Notes the availability and utility of implemented software for various metagenomic tasks.

Conclusions:

  • Metagenomics offers transformative insights into microbial world diversity.
  • Bioinformatics is essential for interpreting complex metagenomic datasets.
  • Ongoing development of computational tools is vital for advancing metagenomic research and discovery.