Datasets:
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---
dataset_info:
features:
- name: seq
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 1875591
num_examples: 6000
- name: test
num_bytes: 480997
num_examples: 1332
download_size: 2310262
dataset_size: 2356588
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: apache-2.0
task_categories:
- text-classification
tags:
- chemistry
- biology
- medical
---
# Dataset Card for Metal Ion Binding Dataset
### Dataset Summary
Metal ion binding sites within proteins play a crucial role across a spectrum of processes, spanning from physiological to pathological, toxicological, pharmaceutical, and diagnostic. Consequently, the development of precise and efficient methods to identify and characterize these metal ion binding sites in proteins has become an imperative and intricate task for bioinformatics and structural biology.
## Dataset Structure
### Data Instances
For each instance, there is a string representing the protein sequence and an integer label indicating the existence of metal-ion binding site(s) on a given protein sequence. See the [metal ion binding dataset viewer](https://huggingface.co/datasets/Bo1015/metal_ion_binding/viewer) to explore more examples.
```
{'seq':'MEHVIDNFDNIDKCLKCGKPIKVVKLKYIKKKIENIPNSHLINFKYCSKCKRENVIENL'
'label':1}
```
The average for the `seq` and the `label` are provided below:
| Feature | Mean Count |
| ---------- | ---------------- |
| seq | 309 |
| label (0) | 0.5 |
| label (1) | 0.5 |
### Data Fields
- `seq`: a string containing the protein sequence
- `label`: an integer label indicating the existence of metal-ion binding site(s) on a given protein sequence
### Data Splits
The metal ion binding dataset has 2 splits: _train_ and _test_. Below are the statistics of the dataset.
| Dataset Split | Number of Instances in Split |
| ------------- | ------------------------------------------- |
| Train | 6,000 |
| Test | 1,332 |
### Source Data
#### Initial Data Collection and Normalization
We employ data collected from [Cheng et al](https://www.nature.com/articles/s41589-022-01223-z) curated from the Protein Data Bank (PDB).
### 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}
}
``` |