license: cc-by-sa-4.0
task_categories:
- token-classification
tags:
- genomics
- bioinformatics
- dna
- biology
- gene-prediction
- science
- huggingscience
- genome-annotation
- token-classification
pretty_name: Gene Finding
size_categories:
- 1K<n<10K
Dataset Card for Dataset Name
Genomic Dataset
Dataset Details
Dataset Description
Genomic Dataset designed for evaluating and benchmarking gene prediction algorithms. The source of the dataset is the GENCODE 2021 Project which provides high accuracy genen and transcript annotations for human and mouse genomes supported by experiemntal data. This makes it a foundational resource that supports genome biology and clinical genomics applications.
- Curated by: Multiple People
- Funded by [optional]: [More Information Needed]
- Shared by [optional]: DNA-LLM
- Language(s) (NLP): NA
- License: MIT
Dataset Sources [optional]
- Paper [optional]: GENCODE 2021 Paper
Uses
Direct Use
- Gene prediction algorithm benchmarking: Evaluating the performance of computational methods for identifying genes in DNA sequences
- Machine learning model training: Training models for genomic sequence analysis and gene identification
Out-of-Scope Use
- Clinical diagnostics: Not suitable for real-time clinical decision making
- Medical applications: Not intended for direct medical diagnosis or treatment
Dataset Structure
- seq: DNA nucleotide sequence (A, T, G, C) - the input genomic sequence
- labels: Gene annotation labels for the sequence - indicating gene structure elements
Dataset Creation
Curation Rationale
The dataset was created to address the need for standardized benchmarking in computational genomics, specifically:
- Lack of standardized benchmarks: Gene prediction algorithms lacked consistent evaluation metrics
- Quality annotation requirements: Need for high-quality, experimentally validated gene annotations
- Research reproducibility: Providing a common dataset for comparing different approaches
- Algorithm development: Supporting the development of more accurate gene finding methods
Source Data
Data Collection and Processing
- Genomic sequences sourced from the GENCODE 2021 annotation database
Who are the source data producers?
- GENCODE consortium: International collaboration of research institutions
Annotations [optional]
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
Citation
BibTeX:
@article{frankish2021gencode,
title={GENCODE 2021},
author={Frankish, Adam and Diekhans, Mark and Jungreis, Irwin and Lagarde, Julien and Loveland, Jane E and Mudge, Jonathan M and Sisu, Cristina and Wright, James C and Armstrong, Joel and Barnes, If and others},
journal={Nucleic acids research},
volume={49},
number={D1},
pages={D916--D923},
year={2021},
publisher={Oxford University Press}
}
APA:
Frankish, A., Diekhans, M., Jungreis, I., Lagarde, J., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J., Barnes, I., & others. (2021). GENCODE 2021. Nucleic acids research, 49(D1), D916-D923.
Glossary [optional]
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Dataset Card Authors [optional]
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