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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 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 sequencelabel
: a string containing the contact label of each residue pair.msa
: "|" seperated MSA sequencesstr_emb
: AIDO.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 is employed as the initilized dataset.
Licensing Information
The dataset is released under the Apache-2.0 License.
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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