metadata

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 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 is employed as the initilized dataset.

Licensing Information

The dataset is released under the Apache-2.0 License.

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}
}