---
dataset_info:
  features:
  - name: seq
    dtype: string
  - name: label
    sequence:
      sequence: int64
  splits:
  - name: train
    num_bytes: 363996805
    num_examples: 12041
  - name: valid
    num_bytes: 46480456
    num_examples: 1505
  - name: test
    num_bytes: 44762708
    num_examples: 1505
  download_size: 63574265
  dataset_size: 455239969
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:
- token-classification
tags:
- biology
- chemistry
size_categories:
- 1K<n<10K
---
# Dataset Card for Contact Prediction Dataset

### Dataset Summary

Contact map prediction aims to determine whether two residues, $i$ and $j$, are in contact or not, based on their distance with a certain threshold ($<$8 Angstrom). This task is an important part of the early Alphafold version for structural prediction. 

## Dataset Structure

### Data Instances

For each instance, there is a string of the protein sequences, a sequence for the contact labels. Each of the sub-labels "[2, 3]" indicates the 3rd residue are in contact with the 4th residue (start from index 0). See the [Contact map prediction dataset viewer](https://huggingface.co/datasets/Bo1015/contact_prediction_binary/viewer/default/test) to explore more examples.

```
{'seq':'QNLLKNLAASLGRKPFVADKQGVYRLTIDKHLVMLAPHGSELVLRTPIDAPMLREGNNVNVTLLRSLMQQALAWAKRYPQTLVLDDCGQLVLEARLRLQELDTHGLQEVINKQLALLEHLIPQLTP'
'label': [ [ 0, 0 ], [ 0, 1 ], [ 1, 1 ], [ 1, 2 ], [ 1, 3 ], [ 1, 101 ], [ 2, 2 ], [ 2, 3 ], [ 2, 4 ], [ 3, 3 ], [ 3, 4 ], [ 3, 5 ], [ 3, 99 ], [ 3, 100 ], [ 3, 101 ], [ 4, 4 ], [ 4, 5 ], [ 4, 53 ], ...]}
```

The average  for the `seq` and the `label` are provided below:

| Feature    | Mean Count |
| ---------- | ---------------- |
| seq    | 249        |
| label | 1,500             |

### Data Fields

- `seq`: a string containing the protein sequence
- `label`: a string containing the contact label of each residue pair.

### Data Splits

The contact map prediction dataset has 3 splits: _train_, _validation_, and _test_. Below are the statistics of the dataset.

| Dataset Split | Number of Instances in Split                |
| ------------- | ------------------------------------------- |
| Train         | 12,041                              |
| Validation    | 1,505                                      |
| Test          | 1,505                                      |

### Source Data

#### Initial Data Collection and Normalization

The [trRosetta dataset](https://www.pnas.org/doi/10.1073/pnas.1914677117) is employed as the initilized dataset. 


### 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}
}
```