proteinglm/optimal_temperature

Dataset Card for Optimal Temperature Dataset

Dataset Summary

Grasping the catalytic activity of enzymes is pivotal for industrial enzyme design, particularly in predicting the optimal temperature for a given enzyme’s catalytic effect.

Dataset Structure

Data Instances

For each instance, there is a string representing the protein sequence and a float value indicating the optimal temperature for a given enzyme’s catalytic effect. See the optimal temperature dataset viewer to explore more examples.

{'seq':'MEHVIDNFDNIDKCLKCGKPIKVVKLKYIKKKIENIPNSHLINFKYCSKCKRENVIENL'
'label':60.5}

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

Feature	Mean Count
seq	467
label (0)	50.0

Data Fields

• seq: a string containing the protein sequence
• label: a float value indicating the optimal temperature for a given enzyme’s catalytic effect.

Data Splits

The Optimal Temperature dataset has 2 splits: train and test. Below are the statistics of the dataset.

Dataset Split	Number of Instances in Split
Train	1,706
Test	190

Source Data

Initial Data Collection and Normalization

The dataset utilized for this task is primarily procured by DeepET, a recent advancement in the field that uses deep learning techniques to understand enzyme thermal adaptation.

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}
}