| | --- |
| | license: apache-2.0 |
| |
|
| | extra_gated_description: "The email provided must have an .edu domain in order to grant access to the data." |
| | extra_gated_fields: |
| | Full name: text |
| | Email: text |
| | Affliation: text |
| | Country/region of residence: country |
| | Supervisor: text |
| | Contact of supervisor: text |
| | I want to use this dataset for: |
| | type: select |
| | options: |
| | - Research |
| | - Education |
| | - label: Other |
| | value: other |
| | I agree to use this dataset for non-commercial use ONLY: checkbox |
| |
|
| | --- |
| | |
| | ## About |
| |
|
| | RhoFold+ is a deep learning model for accurately predicting RNA 3D structures from input sequences. |
| | It uses evolutionary information from MSA as well as embeddings from our pre-trained large RNA language model, RNA-FM. |
| | The work has been published in Nature Methods (<a href='https://www.nature.com/articles/s41592-024-02487-0'>full text available</a>). |
| | This huggingface repository contains the data used for training the RhoFold model, which can be applied by filling in the form. |
| |
|
| | The full codes associated with the data are available at GitHub: |
| | - Official repository: https://github.com/ml4bio/RhoFold |
| | - Official protocol: https://github.com/WangJiuming/rhofold_protocol |
| | |
| | ## Citation |
| | |
| | If you use the data or model in your research, please cite our paper with the following. |
| | |
| | ``` |
| | @article{shen2024accurate, |
| | title={Accurate RNA 3D structure prediction using a language model-based deep learning approach}, |
| | author={Shen, Tao and Hu, Zhihang and Sun, Siqi and Liu, Di and Wong, Felix and Wang, Jiuming and Chen, Jiayang and Wang, Yixuan and Hong, Liang and Xiao, Jin and others}, |
| | journal={Nature Methods}, |
| | pages={1--12}, |
| | year={2024}, |
| | publisher={Nature Publishing Group US New York} |
| | } |
| | ``` |
| | |
