GenBank® is the NIH genetic sequence database, an annotated collection of all publicly available DNA sequences. GenBank is part of the International Nucleotide Sequence Database Collaboration (INSDC), which comprises the DNA DataBank of Japan (DDBJ), the European Nucleotide Archive (ENA), and GenBank at NCBI. These three organizations exchange data on a daily basis.
This dataset has been processed into a parquet format suitable for machine learning training, consisting of genomic sequences and their corresponding accessions. Note that compared to RefSeq, GenBank is redundant and contains sequences exactly as submitted by authors.
This dataset can be used to train massive genomic foundational models, perform broad sequence classification, or study genetic diversity.
The data is genomic sequence data (DNA/RNA) represented as strings of nucleotides (A, C, G, T, N).
Each instance in the dataset represents a sequence of nucleotides.
{
"accession": "U49845.1_part1",
"sequence": "GATCGATCGATC..."
}
accession: The NCBI access identifier for the sequence (e.g., U49845.1). Large sequences may be partitioned with _partXXX suffixes to limit chunk sizes.sequence: The raw nucleotide sequence strings.The dataset is provided as a single train split containing all sequences.
GenBank is designed to provide and encourage access within the scientific community to the most up-to-date and comprehensive DNA sequence information.
Genomic datasets can have a profound impact on medical research, drug discovery, and biological understanding. GenBank's sheer scale allows for the study of unprecedented biological diversity.
GenBank is completely dependent on submissions from the scientific community. Therefore, species that are heavily researched or sequenced frequently are significantly overrepresented.
The database is housed and maintained by the National Center for Biotechnology Information (NCBI).
Data from NCBI GenBank is in the public domain and freely available for use.
This dataset (GenBank Release 272) was retrieved and optimally processed by huggingworld. The sequence data has been specifically serialized into parquet format using the latest pyarrow standards, targeted specifically for ML Research and massive-scale model training. If you utilize this processed version of the dataset in your research or applications, please cite or acknowledge this repository.
@misc{huggingworld2026ncbigenbank,
author = {huggingworld},
title = {NCBI GenBank Complete (Release 271) April 15 2026 - Processed for ML Research},
year = {2026},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/pulmo/ncbi-genbank-complete}}
}
@article{10.1093/nar/gks1195,
author = {Benson, Dennis A. and Cavanaugh, Mark and Clark, Karen and Karsch-Mizrachi, Ilene and Lipman, David J. and Ostell, James and Sayers, Eric W.},
title = "{GenBank}",
journal = {Nucleic Acids Research},
volume = {41},
number = {D1},
pages = {D36-D42},
year = {2012},
month = {11},
issn = {0305-1048},
doi = {10.1093/nar/gks1195},
url = {https://doi.org/10.1093/nar/gks1195},
eprint = {https://huggingface.co/datasets/pulmo/ncbi-genbank-complete/resolve/main/gks1195.pdf},
}
GenBank® is the NIH genetic sequence database, an annotated collection of all publicly available DNA sequences. GenBank is part of the International Nucleotide Sequence Database Collaboration (INSDC), which comprises the DNA DataBank of Japan (DDBJ), the European Nucleotide Archive (ENA), and GenBank at NCBI. These three organizations exchange data on a daily basis.
This dataset has been processed into a parquet format suitable for machine learning training, consisting of genomic sequences and their corresponding accessions. Note that compared to RefSeq, GenBank is redundant and contains sequences exactly as submitted by authors.
This dataset can be used to train massive genomic foundational models, perform broad sequence classification, or study genetic diversity.
The data is genomic sequence data (DNA/RNA) represented as strings of nucleotides (A, C, G, T, N).
Each instance in the dataset represents a sequence of nucleotides.
{
"accession": "U49845.1_part1",
"sequence": "GATCGATCGATC..."
}
accession: The NCBI access identifier for the sequence (e.g., U49845.1). Large sequences may be partitioned with _partXXX suffixes to limit chunk sizes.sequence: The raw nucleotide sequence strings.The dataset is provided as a single train split containing all sequences.
GenBank is designed to provide and encourage access within the scientific community to the most up-to-date and comprehensive DNA sequence information.
Genomic datasets can have a profound impact on medical research, drug discovery, and biological understanding. GenBank's sheer scale allows for the study of unprecedented biological diversity.
GenBank is completely dependent on submissions from the scientific community. Therefore, species that are heavily researched or sequenced frequently are significantly overrepresented.
The database is housed and maintained by the National Center for Biotechnology Information (NCBI).
Data from NCBI GenBank is in the public domain and freely available for use.
This dataset (GenBank Release 272) was retrieved and optimally processed by huggingworld. The sequence data has been specifically serialized into parquet format using the latest pyarrow standards, targeted specifically for ML Research and massive-scale model training. If you utilize this processed version of the dataset in your research or applications, please cite or acknowledge this repository.
@misc{huggingworld2026ncbigenbank,
author = {huggingworld},
title = {NCBI GenBank Complete (Release 271) April 15 2026 - Processed for ML Research},
year = {2026},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/pulmo/ncbi-genbank-complete}}
}
@article{10.1093/nar/gks1195,
author = {Benson, Dennis A. and Cavanaugh, Mark and Clark, Karen and Karsch-Mizrachi, Ilene and Lipman, David J. and Ostell, James and Sayers, Eric W.},
title = "{GenBank}",
journal = {Nucleic Acids Research},
volume = {41},
number = {D1},
pages = {D36-D42},
year = {2012},
month = {11},
issn = {0305-1048},
doi = {10.1093/nar/gks1195},
url = {https://doi.org/10.1093/nar/gks1195},
eprint = {https://huggingface.co/datasets/pulmo/ncbi-genbank-complete/resolve/main/gks1195.pdf},
}