Persistent Mayer homology and persistent Mayer Laplacian is a research paper published in Foundations of Data Science (2024). On theSindex it has a DataRank of 0. It has been cited 15 times.
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NIGMS NIH HHS
Grant: R01 GM126189
NIGMS NIH HHS
Grant: R35 GM148196
NIAID NIH HHS
Grant: R01 AI164266
National Science Foundation
Grant: 1900473
III: Medium: De Rham-Hodge theory modeling and learning of biomolecular data
National Institutes of Health
Grant: 1R01AI164266-01A1
AI-based platform for predicting emerging vaccine-escape variants and designing mutation-proof antibodies
National Institutes of Health
Grant: 5R35GM148196-02
Discovery-Driven Mathematics and Artificial Intelligence for Biosciences and Drug Discovery
National Science Foundation
Grant: 2052983
Collaborative Research: Integrating Algebraic Topology, Graph Theory, and Multiscale Analysis for Learning Complex and Diverse Datasets
National Institutes of Health
Grant: 5R01GM126189-03
Synergistic integration of topology and machine learning for the predictions of protein-ligand binding affinities and mutation impacts
National Science Foundation
Grant: 1761320
Kinetics-Driven Drug Discovery Using Persistent Homology, Rare-Event Molecular Dynamics and Experimental Data
FWCI
3.57
Citation Percentile
0.9%
Citation Trend
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