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

The Central Dogma01:20

The Central Dogma

The central dogma explains the flow of genetic information from DNA nucleotides to the amino acid sequence of proteins.
RNA is the Missing Link Between DNA and Proteins
In the early 1900s, scientists discovered that DNA stores all the information needed for cellular functions and that proteins perform most of these functions. However, the mechanisms of converting genetic information into functional proteins remained unknown for many years. Initially, it was believed that a single gene is...
The Central Dogma01:25

The Central Dogma

Overview
From DNA to Protein03:06

From DNA to Protein

The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...
DNA as a Genetic Template02:05

DNA as a Genetic Template

Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
DNA as a Genetic Template02:05

DNA as a Genetic Template

Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
Operon Model01:23

Operon Model

The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...

You might also read

Related Articles

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

Sort by
Same author

How the Entanglement of Chance and Selection Leads to Darwinian Evolution.

BioEssays : news and reviews in molecular, cellular and developmental biology·2026
Same author

Eukaryogenesis Meets Constructive Neutral Evolution?

BioEssays : news and reviews in molecular, cellular and developmental biology·2026
Same author

Stunning Intricacies of RNA Editing Complexes RECC, RESC, and REH2C: Functional Organization, Developmental Regulation, and Evolutionary History in Kinetoplastid Protists.

Wiley interdisciplinary reviews. RNA·2026
Same author

Eukaryogenesis: Did an Oxidative Crucible Result in Misleading Bioinformatic Analyses?

BioEssays : news and reviews in molecular, cellular and developmental biology·2026
Same author

Provable and Verifiable Quantum Advantage in Sample Complexity.

Physical review letters·2026
Same author

VUScope: a mathematical model for evaluating image-based drug response measurements and predicting long-term incubation outcomes.

Bioinformatics (Oxford, England)·2026
Same journal

Sensing Underwater: Diversifying Selection, Convergent Evolution and Inactivation in Sensory Receptors' Genes of Aquatic Mammals.

Journal of molecular evolution·2026
Same journal

Synonymous Codons as Potential Contributors to Chromatin Stability and Gene Body Methylation in Plants.

Journal of molecular evolution·2026
Same journal

Convergent Functional Genomic Evolution Underlying Repeated Freshwater Colonization in Cetaceans.

Journal of molecular evolution·2026
Same journal

Conditions Enabling the Persistence of Cooperating Synthetase, Ligase, and Mutation-Inhibitor Catalytic Polymers.

Journal of molecular evolution·2026
Same journal

Lineage-Specific Diversification of Nucleoporin Nup98 Genes in Ciliates and Its Evolutionary Implications for the Nuclear Dualism.

Journal of molecular evolution·2026
Same journal

Mitochondrial Genome Evolution: The Influence of Partitioning, Calibration, and Gene Heterogeneity on Pleurodontan Substitution Rates.

Journal of molecular evolution·2026
See all related articles

Related Experiment Video

Updated: May 9, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

A realistic model under which the genetic code is optimal.

Harry Buhrman1, Peter T S van der Gulik, Gunnar W Klau

  • 1Centrum Wiskunde & Informatica (CWI), P.O. Box 94079, 1090 GB, Amsterdam, The Netherlands.

Journal of Molecular Evolution
|July 24, 2013
PubMed
Summary
This summary is machine-generated.

The standard genetic code is optimal for error robustness, according to new calculations. This finding, based on amino acid properties and biosynthetic relationships, suggests the genetic code evolved for stability.

More Related Videos

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System
11:47

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System

Published on: August 1, 2016

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Related Experiment Videos

Last Updated: May 9, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System
11:47

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System

Published on: August 1, 2016

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Area of Science:

  • Biochemistry
  • Genetics
  • Evolutionary Biology

Background:

  • The genetic code exhibits significant error robustness, crucial for biological function.
  • Quantifying this robustness involves analyzing amino acid properties and codon assignments.

Purpose of the Study:

  • To quantify the error robustness of the standard genetic code.
  • To determine if the standard genetic code is optimal in terms of error robustness.

Main Methods:

  • Utilized hydrophobicity scales and polar requirement values for amino acid characterization.
  • Employed a mean square measure to quantify error robustness.
  • Compared the standard code's robustness against random permutations, with constrained assignments based on aptamer considerations and biosynthetic relationships.

Main Results:

  • The standard genetic code was found to be optimal in error robustness.
  • Updated polar requirement values and biosynthetic relations were key inputs.
  • A subdivision approach, grouping amino acids into subgroups, refined the analysis.

Conclusions:

  • The study provides strong evidence for the optimality of the standard genetic code's error robustness.
  • Biosynthetic relationships play a critical role in the evolution of the genetic code.
  • Re-examined theories on code robustness, favoring a hypothesis emphasizing biosynthetic pathways and gradual evolution from simpler forms.