Hugging Face's logo

Datasets:
adibvafa
/
CodonTransformer

Modalities:
Tabular
Text
Formats:
csv
Size:
1M - 10M
Tags:
DNA Sequences
Protein Sequences
Computational Biology
Bioinformatics
Synthetic Biology
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
1
CodonTransformer / README.md
adibvafa's picture
adibvafa
Update README.md
a546903 verified
preview code
|
raw
history blame
2.8 kB
metadata
license:
  - cc-by-4.0
size_categories:
  - 1M<n<10M
tags:
  - DNA Sequences
  - Protein Sequences
  - Computational Biology
  - Bioinformatics
  - Synthetic Biology

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
  • 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 Fallahpour1,2*, Vincent Gureghian3*, Guillaume J. Filion2, Ariel B. Lindner3, Amir Pandi3‡

1 Vector Institute for Artificial Intelligence, Toronto ON, Canada
2 University of Toronto Scarborough; Department of Biological Science; Scarborough ON, Canada
3 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: amir.pandi@cri-paris.org

Additional Resources