Web17. aug 2024 · Persistent homology is constrained to purely topological persistence, while multiscale graphs account only for geometric information. This work introduces persistent spectral theo Web1. sep 2024 · Here, we developed Epistatic Net (EN), a method for spectral regularization of DNNs that exploits evidence that epistatic interactions in many fitness functions are sparse. We built a scalable...
HERMES: Persistent spectral graph software
Web9. apr 2024 · The persistent theories based on hypergraphs perform well in molecular representations for drug design and protein-ligand binding affinity prediction [128, 130]. The neighborhood complex has been ... Web21. dec 2024 · Persistent homology (PH) is one of the most popular tools in topological data analysis (TDA), while graph theory has had a significant impact on data science. Our … grand ole opry family
Persistent spectral theory-guided protein engineering Nature ...
Web7. máj 2024 · Persistent spectral-based machine learning (PerSpect ML) for protein-ligand binding affinity prediction Persistent spectral-based machine learning (PerSpect ML) for protein-ligand binding affinity prediction Sci Adv. 2024 May 7;7 (19):eabc5329. doi: 10.1126/sciadv.abc5329. Print 2024 May. Authors Zhenyu Meng 1 , Kelin Xia 2 Affiliations Web3. feb 2024 · We consider 11 persistent spectral variables and use them as the feature for machine learning models in protein-ligand binding affinity prediction. We systematically … Web21. dec 2024 · Persistent homology (PH) is one of the most popular tools in topological data analysis (TDA), while graph theory has had a significant impact on data science. Our earlier work introduced the persistent spectral graph (PSG) theory as a unified multiscale paradigm to encompass TDA and geometric analysis. grand ole opry from the 50\u0027s