|
--- |
|
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} |
|
} |
|
``` |