Войти
аналитика - Protein Structure Prediction
SGNet: Protein Folding with Deep Learning for Symmetrical Complexes
The author proposes SGNet, a protein folding framework leveraging deep learning to model symmetrical protein complexes. By addressing challenges like sequence length and label assignment ambiguity, SGNet demonstrates improved performance in predicting global symmetry types.
SGNet: Deep Learning for Symmetrical Protein Complex Folding
Proposing SGNet for modeling symmetrical protein structures, leveraging relative position maps and symmetry generators.
SGNet: Protein Folding Framework with Deep Learning
Deep learning framework SGNet models symmetrical protein complexes effectively, addressing challenges in structure determination.
SGNet: Protein Folding in Symmetrical Complexes with Deep Learning
SGNet proposes a protein folding framework to model symmetrical protein assemblies, addressing challenges in structure determination.
Продукты | Ресурсы
© 2024 by Linnk AI