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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - en
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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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+ task_categories:
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+ - token-classification
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+ ---
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+
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+ # CodonTransformer Dataset
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+
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+ A comprehensive collection of DNA and protein sequence pairs from a diverse range of organisms, suitable for various computational biology and bioinformatics applications.
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+
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+ ## Dataset Summary
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+
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+ The CodonTransformer dataset is a large-scale compilation of 1,001,197 DNA sequences and their corresponding protein translations, sourced from 164 different organisms across Eukaryotes, Bacteria, and Archaea. This dataset provides a rich resource for studying gene sequences, codon usage, and protein expression across diverse species.
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+
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+ ## Dataset Contents
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+
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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
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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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+
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+ ## Data Collection and Preprocessing
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+
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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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+
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+ ## Dataset Structure
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+
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+ Each entry contains:
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+ - DNA sequence
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+ - Corresponding protein sequence
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+ - Organism information
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+
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+ ## Uses and Applications
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+
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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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+
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+ It has been used to train the CodonTransformer model for codon optimization tasks.
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+
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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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+
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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: **amir.pandi@cri-paris.org** <br>
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+
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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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+
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+ - **GitHub Repository** <br>
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+ https://github.com/Adibvafa/CodonTransformer
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+
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+ - **Google Colab Demo** <br>
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+ https://adibvafa.github.io/CodonTransformer/GoogleColab
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+
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+ - **PyPI Package** <br>
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+ https://pypi.org/project/CodonTransformer/
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+
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+ - **Paper** <br>
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+ TBD