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Pengkang Guo

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Articles

Enhancing protein graph representations through static-dynamic fusion

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By Bruno E. Correia, Pierre Vandergheynst, Daniel Probst, Pengkang Guo
| BioRxiv
Abstract Machine learning for protein modeling faces significant challenges due to proteins' inherently dynamic nature, yet most graph-based machine learning methods rely solely on static structural information. Recently, the growing availability of molecular dynamics trajectories provides new opportunities for understanding the dynamic behavior of proteins; however, computational methods for utilizing this dynamic information remain limited.
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