Datasets:
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---
dataset_info:
features:
- name: seq
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 986536
num_examples: 19526
- name: test
num_bytes: 227922
num_examples: 4485
download_size: 458823
dataset_size: 1214458
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
task_categories:
- text-classification
tags:
- chemistry
- biology
size_categories:
- 10K<n<100K
---
# Dataset Card for TCR_pMHC_Affinity Dataset
### Dataset Summary
The interaction between T cell receptors (TCRs) and peptide-major histocompatibility complexes (pMHCs) plays a crucial role in the recognition and activation of T cells in the immune system. TCRs are cell surface receptors found on T cells, and pMHCs are complexes formed by peptides derived from antigens bound to major histocompatibility complexes (MHCs) on the surface of antigen-presenting cells. The classification task is to predict whether a given paired TCR sequence and peptide can bind or not.
## Dataset Structure
### Data Instances
For each instance, there is a string representing the protein sequence and an integer label indicating whether a given paired TCR sequence and peptide can bind or not. See the [TCR_pMHC_Affinity dataset viewer](https://huggingface.co/datasets/Bo1015/tcr_pmhc_affinity/viewer) to explore more examples.
```
{'seq':'CAGADGGSQGNLIF|CASSTRSTDTQYF|GILGFVFTL'
'label':1}
```
The average for the `seq` and the `label` are provided below:
| Feature | Mean Count |
| ---------- | ---------------- |
| seq | 39 |
| label (0) | 0.83 |
| label (1) | 0.17 |
### Data Fields
- `seq`: a string containing the protein sequence
- `label`: an integer label indicating whether a given paired TCR sequence and peptide can bind or not.
### Data Splits
The TCR_pMHC_Affinity dataset has 2 splits: _train_ and _test_. Below are the statistics of the dataset.
| Dataset Split | Number of Instances in Split |
| ------------- | ------------------------------------------- |
| Train | 19,526 |
| Test | 4,485 |
### Source Data
#### Initial Data Collection and Normalization
The dataset is major from [VDJdb](https://vdjdb.cdr3.net/), processed and curated from [epiTCR](https://academic.oup.com/bioinformatics/article/39/5/btad284/7140137).
### Citation
If you find our work useful, please consider citing the following paper:
```
@misc{chen2024xtrimopglm,
title={xTrimoPGLM: unified 100B-scale pre-trained transformer for deciphering the language of protein},
author={Chen, Bo and Cheng, Xingyi and Li, Pan and Geng, Yangli-ao and Gong, Jing and Li, Shen and Bei, Zhilei and Tan, Xu and Wang, Boyan and Zeng, Xin and others},
year={2024},
eprint={2401.06199},
archivePrefix={arXiv},
primaryClass={cs.CL},
note={arXiv preprint arXiv:2401.06199}
}
``` |