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