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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.

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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

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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