You're currently viewing an old version of this dataset. To see the current version, click here.

SGNet: Folding Symmetrical Protein Complex with Deep Learning

The SGNet dataset is a benchmark for symmetrical protein complex structure prediction. It contains a set of symmetrical protein complexes with different symmetry types (C, D, T, O, I). The dataset is used to evaluate the performance of the SGNet model in predicting symmetrical protein complex structures.

Data and Resources

Cite this as

Zhaoqun Li, Jingcheng Yu, Qiwei Ye (2024). Dataset: SGNet: Folding Symmetrical Protein Complex with Deep Learning. https://doi.org/10.57702/i0alhpxy

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2403.04395
Author Zhaoqun Li
More Authors
Jingcheng Yu
Qiwei Ye