| | --- |
| | license: other |
| | --- |
| | # CryoZeta |
| |
|
| | CryoZeta is a de novo macromolecular structure modeling tool that integrates cryo-EM density information with a diffusion-model-based structure prediction pipeline. |
| |
|
| | Kihara Lab website: https://kiharalab.org/ |
| |
|
| | Kihara Lab EM server: https://em.kiharalab.org/algorithm/CryoZeta |
| |
|
| | Github: https://github.com/kiharalab/CryoZeta |
| |
|
| | ## Lincense |
| |
|
| | This repository uses a custom license. See the [LICENSE](LICENSE.md) file for full terms. |
| |
|
| | ## Citations |
| |
|
| | Please cite our paper: |
| |
|
| | ```bibtex |
| | @article{zhang2026accurate, |
| | title = {Accurate macromolecular complex modeling for cryo-EM}, |
| | author = {Zhang, Zicong and Li, Shu and Farheen, Farhanaz and Kagaya, Yuki and Liu, Boyuan and Ibtehaz, Nabil and Terashi, Genki and Nakamura, Tsukasa and Zhu, Han and Khan, Kafi and Zhang, Yuanyuan and Kihara, Daisuke}, |
| | journal = {bioRxiv}, |
| | year = {2026}, |
| | doi = {10.64898/2026.02.13.705846}, |
| | url = {https://www.biorxiv.org/content/10.64898/2026.02.13.705846v1}, |
| | note = {Preprint} |
| | } |
| | ``` |
