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Algebraic graph learning of protein-ligand binding affinity
Duc Duy Nguyen, Guo-Wei Wei
Although algebraic graph theory based models have been widely applied in physical modeling and molecular studies, they are typically incompetent in the analysis and prediction of b…
Divide-and-Conquer Strategy for Large-Scale Eulerian Solvent Excluded Surface
Rundong Zhao, Menglun Wang, Yiying Tong +1
Motivation: Surface generation and visualization are some of the most important tasks in biomolecular modeling and computation. Eulerian solvent excluded surface (ESES) software pr…
Blind prediction of protein B-factor and flexibility
David Bramer, Guo-Wei Wei
Debye-Waller factor, a measure of X-ray attenuation, can be experimentally observed in protein X-ray crystallography. Previous theoretical models have made strong inroads in the an…
Persistent cohomology for data with multicomponent heterogeneous information
Zixuan Cang, Guo-Wei Wei
Persistent homology is a powerful tool for characterizing the topology of a data set at various geometric scales. When applied to the description of molecular structures, persisten…
DG-GL: Differential geometry based geometric learning of molecular datasets
Duc Duy Nguyen, Guo-Wei Wei
Motivation: Despite its great success in various physical modeling, differential geometry (DG) has rarely been devised as a versatile tool for analyzing large, diverse and complex…
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges
Duc Duy Nguyen, Zixuan Cang, Kedi Wu +3
Advanced mathematics, such as multiscale weighted colored graph and element specific persistent homology, and machine learning including deep neural networks were integrated to con…