--- dataset_info: features: - name: seqs dtype: string - name: labels dtype: int64 splits: - name: train num_bytes: 88951983 num_examples: 283057 - name: valid num_bytes: 19213838 num_examples: 62973 - name: test num_bytes: 22317993 num_examples: 73205 download_size: 127755417 dataset_size: 130483814 configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* - split: test path: data/test-* --- # INFORMATION FROM [HERE](https://huggingface.co/datasets/biomap-research/temperature_stability) PLEASE CITE THEIR PAPER BELOW ### Dataset Summary The accurate prediction of protein thermal stability has far-reaching implications in both academic and industrial spheres. This task primarily aims to predict a protein’s capacity to preserve its structural stability under a temperature condition of 65 degrees Celsius. ## Dataset Structure ### Data Instances For each instance, there is a string representing the protein sequence and an integer label indicating whether the protein can maintain its structural stability at a temperature of 65 degrees Celsius. See the [temperature stability dataset viewer](https://huggingface.co/datasets/Bo1015/temperature_stability/viewer) to explore more examples. ``` {'seq':'MEHVIDNFDNIDKCLKCGKPIKVVKLKYIKKKIENIPNSHLINFKYCSKCKRENVIENL' 'label':1} ``` The average for the `seq` and the `label` are provided below: | Feature | Mean Count | | ---------- | ---------------- | | seq | 300 | ### Data Fields - `seq`: a string containing the protein sequence - `label`: an integer label indicating the structural stability of each sequence. ### Data Splits The temperature stability dataset has 3 splits: _train_, _valid_, and _test_. Below are the statistics of the dataset. | Dataset Split | Number of Instances in Split | | ------------- | ------------------------------------------- | | Train | 283,057 | | Valid | 62,973 | | Test | 73,205 | ### Source Data #### Initial Data Collection and Normalization We adapted the dataset strategy from [TemStaPro](https://academic.oup.com/bioinformatics/article/40/4/btae157/7632735). ### Licensing Information The dataset is released under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0). ### 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} } ```