Related Experiment Video
Updated: May 28, 2026
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
Summary
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.
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.
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