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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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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...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...

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Related Experiment Video

Updated: May 7, 2026

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

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Meta4: a web application for sharing and annotating metagenomic gene predictions using web services.

Emily J Richardson1, Franck Escalettes, Ian Fotheringham

  • 1ARK-Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh Easter Bush, Midlothian, UK.

Frontiers in Genetics
|September 19, 2013
PubMed
Summary

Meta4 is a new web application designed for sharing and annotating metagenomic gene predictions. This tool facilitates rapid data interrogation and collaboration for gene discovery projects using whole-genome shotgun metagenomics.

Keywords:
bioinformaticsdatabasegene discoverymetagenomicsweb service

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Whole-genome shotgun metagenomics generates vast amounts of DNA sequence data from ecosystems.
  • Gene discovery necessitates efficient access to homology and domain structure information for millions of proteins.
  • Existing tools lack flexibility and ease of use for sharing and interrogating metagenomic datasets.

Purpose of the Study:

  • To present Meta4, a novel web application for sharing and annotating metagenomic gene predictions.
  • To provide a flexible and extensible platform for collaborative analysis of metagenomic data.
  • To address the need for user-friendly tools in metagenomic gene discovery.

Main Methods:

  • Development of a flexible and extensible web application named Meta4.
  • Utilizing a simple relational database to store proteins and predicted domains.
  • Implementing a dynamic front-end for browser-based results display.
  • Integrating web services for real-time homology searches against public databases.

Main Results:

  • Meta4 enables the sharing and annotation of metagenomic gene predictions.
  • The application stores protein and domain data in an accessible relational database.
  • Web services provide up-to-date homology information, enhancing gene discovery.
  • A cloud image and example implementation are available for accessibility.

Conclusions:

  • Meta4 offers a flexible and extensible solution for metagenomic data sharing and annotation.
  • The tool simplifies the interrogation of metagenomic gene predictions for researchers.
  • Meta4 supports collaborative gene discovery efforts by providing an easy-to-use platform.