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---
license:
- cc-by-4.0
size_categories:
- 1M<n<10M
tags:
- DNA Sequences
- Protein Sequences
- Computational Biology
- Bioinformatics
- Synthetic Biology
---
![image/png](https://github.com/Adibvafa/CodonTransformer/raw/main/src/banner_final.png)
# CodonTransformer Dataset
A comprehensive compilation of 1,001,197 DNA and protein sequence pairs, sourced from 164 organisms across Eukaryotes, Bacteria, and Archaea.
This dataset provides a rich resource for various computational biology and bioinformatics applications such as studying gene sequences, codon usage, and protein expression across diverse species.
## Dataset Contents
- 1,001,197 DNA-protein sequence pairs
- Sequences from 164 organisms, including:
- Eukaryotes: Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Mus musculus, Saccharomyces cerevisiae, Chlamydomonas reinhardtii, Nicotiana tabacum
- Bacteria: Various Enterobacteriaceae species including Escherichia coli
- Archaea: Thermococcus barophilus, Sulfolobus solfataricus
- Chloroplast genomes: Chlamydomonas reinhardtii, Nicotiana tabacum
## Data Collection and Preprocessing
- **Source**: NCBI resources
- **Original Format**: Gene or CDS (Coding Sequence)
- **Protein Sequences**: Translated using NCBI Codon Tables
- **Quality Control**:
- DNA sequences divisible by three in length
- Start with a start codon
- End with a single stop codon
## Dataset Structure
Each entry contains:
- DNA sequence
- Corresponding protein sequence
- Gene and organism information
## Uses and Applications
This dataset is valuable for various research areas and applications, including:
- Comparative genomics
- Codon usage analysis
- Protein expression optimization
- Synthetic biology and genetic engineering
- Machine learning models in bioinformatics
It has been used to train the CodonTransformer model for codon optimization tasks.
## Authors
Adibvafa Fallahpour<sup>1,2</sup>\*, Vincent Gureghian<sup>3</sup>\*, Guillaume J. Filion<sup>2</sup>‡, Ariel B. Lindner<sup>3</sup>‡, Amir Pandi<sup>3</sup>‡
<sup>1</sup> Vector Institute for Artificial Intelligence, Toronto ON, Canada
<sup>2</sup> University of Toronto Scarborough; Department of Biological Science; Scarborough ON, Canada
<sup>3</sup> Université Paris Cité, INSERM U1284, Center for Research and Interdisciplinarity, F-75006 Paris, France
\* These authors contributed equally to this work.
‡ To whom correspondence should be addressed: <br>
guillaume.filion@utoronto.ca, ariel.lindner@inserm.fr, amir.pandi@cri-paris.org
<br>
## Additional Resources
- **Project Website** <br>
https://adibvafa.github.io/CodonTransformer/
- **GitHub Repository** <br>
https://github.com/Adibvafa/CodonTransformer
- **Google Colab Demo** <br>
https://adibvafa.github.io/CodonTransformer/GoogleColab
- **PyPI Package** <br>
https://pypi.org/project/CodonTransformer/
- **Paper** <br>
TBD |