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