MD Simulations and Machine Learning to Quantify Interfacial Hydrophobicity
Applied Algebraic Topology Network via YouTube
Overview
Syllabus
Intro
Combining Molecular Dynamics Simulations and Learning to Quantify Interfacial Hydrophobic
Motivation: Hydrophobicity of idealized and real interfaces
Hydration free energy of cavity as descriptor of hydrophobicity
Density matrices - orientation information
Density matrices-performance compariso
Hydrogen bond graphs
Topological data analysis
Euler Characteristic is stable
Human-selected water order parameters
Feature selection with LASSO regression
Analysis of important features
Acknowledgements
Taught by
Applied Algebraic Topology Network