Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

Microbial communities, comprising bacteria, archaea, and eukaryotic microorganisms, inhabit diverse ecosystems and play crucial roles in environmental and biological processes. Their diversity is defined by three main parameters: species richness (the number of distinct species), species abundance (the relative quantity of each species), and species evenness (how uniformly individual species are distributed in various locations). These factors together shape the structure and ecological balance...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
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...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

In-vitro evaluation of the proliferative and osteogenic activity of atrophic non-union derived mesenchymal stem cells compared to autologous bone graft derived mesenchymal stem cells.

European journal of trauma and emergency surgery : official publication of the European Trauma Society·2026
Same author

Assessment of a novel functional food modulating the microbiota-inflammation-brain axis in patients with heart failure and/or /atrial fibrillation patients (the AMBROSIA study): Protocol for a randomized controlled trial.

Contemporary clinical trials·2025
Same author

Adherence to post-therapeutic multidisciplinary tumor board recommendation and its influence on oncological outcomes in high-risk prostate cancer patients following radical prostatectomy.

International urology and nephrology·2025
Same author

Risky leisure noise exposure during the transition to adulthood and the impact of major life events - results of the OHRKAN cohort study.

International journal of audiology·2024
Same author

CoCoPyE: feature engineering for learning and prediction of genome quality indices.

GigaScience·2024
Same author

A scalable approach for critical care data extraction and analysis in an academic medical center.

International journal of medical informatics·2024

Related Experiment Video

Updated: Jun 1, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

CoMet--a web server for comparative functional profiling of metagenomes.

Thomas Lingner1, Kathrin Petra Asshauer, Fabian Schreiber

  • 1Department of Bioinformatics, Institute for Microbiology and Genetics, Georg-August University Göttingen, Goldschmidtstr. 1, 37077 Göttingen, Germany. thomas@gobics.de

Nucleic Acids Research
|May 31, 2011
PubMed
Summary

This study introduces CoMet, a web server for comparative metagenomics, enabling analysis of microbial communities from short read data. CoMet facilitates understanding genetic similarities and differences in complex microbial ecosystems.

More Related Videos

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

Related Experiment Videos

Last Updated: Jun 1, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Microbial Ecology

Background:

  • High-throughput sequencing generates vast amounts of genomic and metagenomic data.
  • Comparative metagenomics is crucial for understanding microbial community structure and function.
  • Analyzing functional potential requires robust computational tools.

Purpose of the Study:

  • To develop an accessible web server for comparative metagenomics analysis.
  • To facilitate the elucidation of genetic similarities and differences in microbial communities.
  • To provide a user-friendly platform for analyzing large metagenomic datasets.

Main Methods:

  • Development of the CoMet web server (http://comet.gobics.de).
  • Integration of Open Reading Frame (ORF) finding and Pfam domain assignment.
  • Implementation of comparative statistical analyses on protein sequences.

Main Results:

  • CoMet offers an easy-to-use platform for comparative metagenomics.
  • The server analyzes large collections of metagenomic short read data.
  • Provides both tabular data and visual outputs like hierarchical clustering and multi-dimensional scaling plots.

Conclusions:

  • CoMet enables efficient comparative analysis of microbial communities.
  • Visualizations offer a quick overview of metagenomic sample sets.
  • The tool supports biomedical and biological research by analyzing functional potential.