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