metadata

dataset_info:
  features:
    - name: seq
      dtype: string
    - name: label
      sequence: int64
  splits:
    - name: train
      num_bytes: 24941535
      num_examples: 10848
    - name: test
      num_bytes: 1665908
      num_examples: 667
  download_size: 3610640
  dataset_size: 26607443
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
license: apache-2.0
task_categories:
  - token-classification
tags:
  - chemistry
  - biology
size_categories:
  - 10K<n<100K

Dataset Card for Secondary Structure Prediction (Q3) Dataset

Dataset Summary

The study of a protein’s secondary structure (Sec. Struc. P.) forms a fundamental cornerstone in understanding its biological function. This secondary structure, comprising helices, strands, and various turns, bestows the protein with a specific three-dimensional configuration, which is critical for the formation of its tertiary structure. In the context of this work, a given protein sequence is classified into three distinct categories, each representing a different structural element: H - Helix (includes alpha-helix, 3-10 helix, and pi helix), E - Strand (includes beta-strand and beta-bridge), C - Coil (includes turns, bends, and random coils).

Dataset Structure

Data Instances

For each instance, there is a string of the protein sequences, a sequence for the strucutral labels. See the Secondary structure prediction dataset viewer to explore more examples.

{'seq':'MRGSHHHHHHGSVKVKFVSSGEEKEVDTSKIKKVWRNLTKYGTIVQFTYDDNGKTGRGYVRELDAPKELLDMLARAEGKLN'
'label':[ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2 ]}

The average for the seq and the label are provided below:

Feature	Mean Count
seq	256
label (0)	109
label (1)	54
label (2)	92

Data Fields

seq: a string containing the protein sequence
label: a sequence containing the structural label of each residue.

Data Splits

The secondary structure prediction dataset has 2 splits: train and test. Below are the statistics of the dataset.

Dataset Split	Number of Instances in Split
Train	10,848
Test	667

Source Data

Initial Data Collection and Normalization

The datasets applied in this study were originally published by NetSurfP-2.0.

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}
}