Buckets:
| # Dataset Card for Contact Prediction Dataset for RAGProtein | |
| ### 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 ], ...], 'msa': 'QNLLKNLAASLGRKPFVADKQGVYRLTIDKHLVMLAPHGSELVLRTPIDAPMLREGNNVNVTLLRSLMQQALAWAKRYPQTLVLDDCGQLVLEARLRLQELDTHGLQEVINKQLALLEHLIPQLTP|QNLLKNLAASLGRKPFVADKQGVYRLTIDKHLVMLAPHGSELVLRTPIDAPMLREGNNVNVTLLRSLMQQALAWAKRYPQTLVLDDCGQLVLEARLRLQELDTHGLQEVINKQLALLEHLIPQLTP...', 'str_emb': [seq_len, 384]} | |
| ``` | |
| 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. | |
| - `msa`: "|" seperated MSA sequences | |
| - `str_emb`: GB.StructureTokenizer generated structure embedding from AF2 predicted structures | |
| ### 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). | |
| ### Processed data collection | |
| Single sequence data are collected from this 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} | |
| } | |
| ``` |
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