proteinglm/cloning_clf
Dataset Card for Cloning CLF Dataset Dataset Summary Protein structure determination includes a series of experimental stages to yield stable proteins for X-ray crystallography. Specifically, the proteins are first selected and expressed, then purified for crystal structure determination. Each step corresponds to a "stage tag" to denote whether the protein is stable under a certain stage. Dataset Structure Data Instances For each… See the full description on the dataset page: https://huggingface.co/datasets/proteinglm/cloning_clf.
Dataset Card for Cloning CLF Dataset
Dataset Summary
Protein structure determination includes a series of experimental stages to yield stable proteins for X-ray crystallography. Specifically, the proteins are first selected and expressed, then purified for crystal structure determination. Each step corresponds to a "stage tag" to denote whether the protein is stable under a certain stage.
Dataset Structure
Data Instances
For each instance, there is a string representing the protein sequence and an integer label indicating whether a protein sequence is stable under a certain stage. See the Cloning CLF dataset viewer to explore more examples.
{'seq':'MEHVIDNFDNIDKCLKCGKPIKVVKLKYIKKKIENIPNSHLINFKYCSKCKRENVIENL'
'label':1}The average for the seq and the label are provided below:
Data Fields
seq: a string containing the protein sequencelabel: a float value indicating the $k_cat$ score of the protein sequence.
Data Splits
The cloning clf dataset has 2 splits: train and test. Below are the statistics of the dataset.
Source Data
Initial Data Collection and Normalization
The dataset is collected from PredPPCrys, which manually annotated thousands of proteins with different experimental procedures.
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}
}