---
task_categories:
- text-generation
language:
- en
tags:
- proteins
- biology
- uniprot
size_categories:
- 100K<n<1M
---
# Dataset Card for PAIR

This dataset contains all the text annotations we collected and parsed from UniProt Swiss-Prot February 2023 and used to train PAIR -- a simple framework to finetune protein language models using text annotations. You can read more details about PAIR here: https://www.biorxiv.org/content/10.1101/2024.07.22.604688v2.abstract

## Dataset Details

### Dataset Description

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


### Dataset Sources

- **Repository:** (coming soon!)
- **Paper:** https://www.biorxiv.org/content/10.1101/2024.07.22.604688v2.abstract
- **Model checkpoints:** https://huggingface.co/h4duan

## Uses

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

### Example usage

```
from datasets import load_dataset



```
### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

This dataset contains text annotations from Swiss-Prot February 2023; our models were trained on all of them. Please be mindful about potential data leakage from time splits/identical protein sequences on any downstream tasks in your setup.

## 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. -->

[More Information Needed]

## Dataset Creation

### Source Data

This data was collected from the Swiss-Prot checkpoint from February 2023, found here: XXX

#### 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. -->

[More Information Needed]

#### 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. -->

[More Information Needed]

### Annotations

I don't think we did any annotations for parsing only for loading (double check)

#### Personal and Sensitive Information

To our knowledge, this dataset does not contain any private information.

## Bias, Risks, and Limitations

In general, the dataset is highly imbalanced in terms of how many and what protein sequences in Swiss-Prot have an annotation for a given annotation type. This dataset is sparse


## Citation

**BibTeX:**

```
@article{duan2024boosting,
  title={Boosting the Predictive Power of Protein Representations with a Corpus of Text Annotations},
  author={Duan, Haonan and Skreta, Marta and Cotta, Leonardo and Rajaonson, Ella Miray and Dhawan, Nikita and Aspuru-Guzik, Alán and Maddison, Chris J},
  journal={bioRxiv},
  pages={2024--07},
  year={2024},
  publisher={Cold Spring Harbor Laboratory}
}
```

## Dataset Card Authors

[More Information Needed]

## Dataset Card Contact

For any issues with this dataset, please contact `martaskreta@cs.toronto.edu` or `haonand@cs.toronto.edu`