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Related Concept Videos

Translation01:31

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Translation01:31

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
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...
tRNA Activation02:26

tRNA Activation

Aminoacyl-tRNA synthetases are present in both eukaryotes and bacteria. Though eukaryotes have 20 different aminoacyl-tRNA synthetases to couple to 20 amino acids, many bacteria do not have genes for all of these aminoacyl-tRNA synthetases. Despite this, they still use all 20 amino acids to synthesize their proteins. For instance, some bacteria do not have the gene encoding the enzyme that couples glutamine with its partner tRNA. In these organisms, one enzyme adds glutamic acid to all of the...
tRNA Activation02:26

tRNA Activation

Aminoacyl-tRNA synthetases are present in both eukaryotes and bacteria. Though eukaryotes have 20 different aminoacyl-tRNA synthetases to couple to 20 amino acids, many bacteria do not have genes for all of these aminoacyl-tRNA synthetases. Despite this, they still use all 20 amino acids to synthesize their proteins. For instance, some bacteria do not have the gene encoding the enzyme that couples glutamine with its partner tRNA. In these organisms, one enzyme adds glutamic acid to all of the...
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...

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Related Experiment Video

Updated: May 28, 2026

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers
10:41

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Published on: June 24, 2019

Modeling the Language of Codons with Artificial Intelligence.

Claudèle Lemay-St-Denis1, Rachel Kolodny1

  • 1Department of Computer Science, University of Haifa, Haifa, Israel; email: claudele.lemaystdenis@gmail.com, trachel@cs.haifa.ac.il.

Annual Review of Biomedical Data Science
|May 26, 2026
PubMed
Summary
This summary is machine-generated.

Advanced artificial intelligence (AI) models analyze messenger RNA (mRNA) codon sequences to understand protein expression and molecular evolution. These AI tools help design better mRNA sequences for improved protein production and stability.

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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

Related Experiment Videos

Last Updated: May 28, 2026

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers
10:41

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Published on: June 24, 2019

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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Messenger RNA (mRNA) codon sequences are crucial for protein expression.
  • Species-specific codon usage impacts mRNA stability, translation, and protein folding.
  • Identifying complex patterns in codon sequences requires advanced computational methods.

Purpose of the Study:

  • To review recent advancements in artificial intelligence (AI) models for codon-level sequence analysis.
  • To explore the application of AI in understanding mRNA sequence signals and their impact.
  • To highlight the use of AI in designing novel mRNA sequences and recoding proteins.

Main Methods:

  • Review of discriminative and generative artificial intelligence (AI) models.
  • Analysis of codon language models for prediction tasks.
  • Examination of generative models for sequence design and protein recoding.

Main Results:

  • AI models can identify statistical patterns in evolutionarily selected codon sequences.
  • Codon-based AI models are effective for predicting mRNA properties and designing sequences.
  • These models offer insights into molecular evolution and protein expression optimization.

Conclusions:

  • Artificial intelligence (AI) is a powerful tool for deciphering codon sequences and their biological functions.
  • AI-driven approaches are advancing heterologous protein expression and mRNA stability.
  • Further research in codon-based AI holds significant potential for molecular biology and synthetic biology.