---
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

<!-- Provide a longer summary of what this dataset is. -->

Genomic Dataset designed for evaluating and benchmarking gene prediction algorithms. The source of the dataset is the [GENCODE 2021 Project](https://watermark02.silverchair.com/gkaa1087.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAA1MwggNPBgkqhkiG9w0BBwagggNAMIIDPAIBADCCAzUGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQM9pw3GLRMhtZvcWWIAgEQgIIDBtP1R80Xq87yoSgbVEPGW20YHDCG4gdw2DhHcDlxsJPiqIM_JPa9033FbiH4JY5ypci9GSXWA73Gp9ZX_Nsl7YKApfYEhCBO2s9RfUV_EV2bk6HdDKQBxa4_UHPNyRjfrWGNhGWV-oukuc4v8Zt2nkoH14o0OrMC0VaJ2gj3OTQGBLZUC7ZpY-kfEPT71VoeHhb53RRYx6JlA4qk_kXS06N4b9xRkKHtFPO1qW2l9tFShy8VUKXtPYi7B49qAYginTIXgmVeRUGXbBodVevB3mODTGPesZdi6er0P64BPCY-hrips1CuGZiCe1J4nBWLxso3eMiKoEgJAy-_O0w_2Mr6KW9qoyjgz0KEotZhZNE_XZOXqYhwcLbkOTCkXppLKKf7ukEewBjWqZUPjWbmfbK1brtBmOqob2eimPXAWC1cBwF6MU6hHlq9uKIXXF4_SC2SaCR4ptlpIsbDtRXzf1H7Z-3JDx_rxwP5IU8Dw5jcUmbvWOLf8Ke7xvERCYvX9kLkbMjuGjGztZSSvQWnonxAui2LN8OPAaVSME9xkEf6j8Xsp61lssP6LcY--Len8gmk61MypGNjND0pQMQW3bleiJ5QMLFfHYad_1vDvKNyv0kzSfRlCq407hEE7jilOcd8lrhdbJzGKmZUy1LQCHpTDaDKhO-4MFH5ds-3N_3wL5tICqpQ_-13QivNJKNX0XC9cT3EG2N73IyS5_lZs7obdzbN_4gUcLgqrHYMDO0RxTEz3WIO_FTnSgjK9N9Kf7-3uZubxOYz6nMCGzzADd45lafim943u1DcPSCkOL4mKpfzKvRduf_VEdIq8S-cC-oxiw_leOduiXHT005C4UQXGMBOWam0TUtQ6Qu2pcLincTCd-ysoExjnuGzgTvicKbla2Pl9BXQXfIz48mBMaA0gXYW-jWxNnV2W973b8kXaR_PBEIjUdOqJJkWaMl6XIy96x6sD48YluDRQhaNvRLCv55pzmoUmuaiiIjD6LC0RyrdZSosJbo7uv76rTJptZHpupOEWg) 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]

<!-- Provide the basic links for the dataset. -->

- **Paper [optional]:** [GENCODE 2021 Paper](https://huggingface.co/datasets/DNA-LLM/gene_finding_benchmark_v1/new/main?filename=README.md)

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->
- **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

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
- **Clinical diagnostics:** Not suitable for real-time clinical decision making
- **Medical applications:** Not intended for direct medical diagnosis or treatment

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

- **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

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

- Genomic sequences sourced from the GENCODE 2021 annotation database

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
- **GENCODE consortium:** International collaboration of research institutions


### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

```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]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Dataset Card Authors [optional]

[More Information Needed]

## Dataset Card Contact

[More Information Needed]