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--- |
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dataset_info: |
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features: |
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- name: seq |
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dtype: string |
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- name: label |
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sequence: |
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sequence: int64 |
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splits: |
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- name: train |
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num_bytes: 363996805 |
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num_examples: 12041 |
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- name: valid |
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num_bytes: 46480456 |
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num_examples: 1505 |
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- name: test |
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num_bytes: 44762708 |
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num_examples: 1505 |
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download_size: 63574265 |
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dataset_size: 455239969 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: valid |
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path: data/valid-* |
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- split: test |
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path: data/test-* |
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license: apache-2.0 |
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task_categories: |
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- token-classification |
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tags: |
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- biology |
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- chemistry |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Card for Contact Prediction Dataset |
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### Dataset Summary |
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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. |
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## Dataset Structure |
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### Data Instances |
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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. |
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``` |
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{'seq':'QNLLKNLAASLGRKPFVADKQGVYRLTIDKHLVMLAPHGSELVLRTPIDAPMLREGNNVNVTLLRSLMQQALAWAKRYPQTLVLDDCGQLVLEARLRLQELDTHGLQEVINKQLALLEHLIPQLTP' |
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'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 ], ...]} |
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``` |
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The average for the `seq` and the `label` are provided below: |
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| Feature | Mean Count | |
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| ---------- | ---------------- | |
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| seq | 249 | |
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| label | 1,500 | |
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### Data Fields |
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- `seq`: a string containing the protein sequence |
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- `label`: a string containing the contact label of each residue pair. |
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### Data Splits |
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The contact map prediction dataset has 3 splits: _train_, _validation_, and _test_. Below are the statistics of the dataset. |
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| Dataset Split | Number of Instances in Split | |
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| ------------- | ------------------------------------------- | |
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| Train | 12,041 | |
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| Validation | 1,505 | |
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| Test | 1,505 | |
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### Source Data |
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#### Initial Data Collection and Normalization |
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The [trRosetta dataset](https://www.pnas.org/doi/10.1073/pnas.1914677117) is employed as the initilized dataset. |
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### Licensing Information |
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The dataset is released under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0). |
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### Citation |
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If you find our work useful, please consider citing the following paper: |
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``` |
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@misc{chen2024xtrimopglm, |
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title={xTrimoPGLM: unified 100B-scale pre-trained transformer for deciphering the language of protein}, |
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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}, |
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year={2024}, |
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eprint={2401.06199}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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note={arXiv preprint arXiv:2401.06199} |
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} |
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``` |
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