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---
dataset_info:
features:
- name: seq
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 88951983
num_examples: 283057
- name: valid
num_bytes: 19213838
num_examples: 62973
- name: test
num_bytes: 22317993
num_examples: 73205
download_size: 127753697
dataset_size: 130483814
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
license: apache-2.0
task_categories:
- text-classification
tags:
- chemistry
- biology
size_categories:
- 100K<n<1M
---
# Dataset Card for Temperature Stability Dataset
### Dataset Summary
The accurate prediction of protein thermal stability has far-reaching implications in both academic and industrial spheres. This task primarily aims to predict a protein’s capacity to preserve its structural stability under a temperature condition of 65 degrees Celsius.
## Dataset Structure
### Data Instances
For each instance, there is a string representing the protein sequence and an integer label indicating whether the protein can maintain its structural stability at a temperature of 65 degrees Celsius. See the [temperature stability dataset viewer](https://huggingface.co./datasets/Bo1015/temperature_stability/viewer) to explore more examples.
```
{'seq':'MEHVIDNFDNIDKCLKCGKPIKVVKLKYIKKKIENIPNSHLINFKYCSKCKRENVIENL'
'label':1}
```
The average for the `seq` and the `label` are provided below:
| Feature | Mean Count |
| ---------- | ---------------- |
| seq | 300 |
### Data Fields
- `seq`: a string containing the protein sequence
- `label`: an integer label indicating the structural stability of each sequence.
### Data Splits
The temperature stability dataset has 3 splits: _train_, _valid_, and _test_. Below are the statistics of the dataset.
| Dataset Split | Number of Instances in Split |
| ------------- | ------------------------------------------- |
| Train | 283,057 |
| Valid | 62,973 |
| Test | 73,205 |
### Source Data
#### Initial Data Collection and Normalization
We adapted the dataset strategy from [TemStaPro](https://academic.oup.com/bioinformatics/article/40/4/btae157/7632735).
### Licensing Information
The dataset is released under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0).
### 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}
}
```