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Related Concept Videos

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
Gene Families01:57

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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 Conversion02:08

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...
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 Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
Gene Conversion02:08

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...

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Related Experiment Video

Updated: May 15, 2026

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity
12:42

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

Published on: April 13, 2012

GO for gene documents.

Padmini Srinivasan1, Xin Ying Qiu

  • 1School of Library and Information Science, University of Iowa, Iowa City, IA, USA. padmini-srinivasan@uiowa.edu

BMC Bioinformatics
|December 6, 2007
PubMed
Summary
This summary is machine-generated.

This study developed automatic methods for Gene Ontology (GO) annotation using biomedical literature, achieving moderate success with Support Vector Machines (SVMs). The findings highlight the complexity of GO annotation and the potential of automated approaches.

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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

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Related Experiment Videos

Last Updated: May 15, 2026

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity
12:42

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

Published on: April 13, 2012

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Gene Ontology (GO) annotation is crucial for understanding gene function.
  • Manual GO annotation is time-consuming and expensive.
  • Automated methods using biomedical literature can supplement manual efforts.

Purpose of the Study:

  • To develop and evaluate automatic gene and product annotation methods using the biomedical literature.
  • To assess the effectiveness of Support Vector Machines (SVM) classifiers for GO annotation.
  • To investigate the impact of different strategies on annotation performance.

Main Methods:

  • Utilized a set of Support Vector Machines (SVM) classifiers.
  • Evaluated performance across GO hierarchies: molecular function, cellular component, and biological process.
  • Investigated the impact of term weighting, feature selection, and thresholding strategies.
  • Explored the exploitation of hierarchical structures and classification correctness criteria.

Main Results:

  • Achieved F-scores of 0.49 (molecular function), 0.41 (cellular component), and 0.33 (biological process).
  • Feature selection strategies decreased performance; term weighting strategies showed no significant difference.
  • A single threshold per hierarchy was optimal; hierarchy level impacted performance.
  • Classifiers for rare codes are possible but incur significant performance penalties.

Conclusions:

  • The Gene Ontology annotation problem is complex.
  • Topic drift is a key consideration for annotation strategies.
  • Automated methods show promise but face challenges, particularly with limited data.