Overview
Explore molecular dynamics simulations using Python's scientific ecosystem, focusing on OpenMM and its tools. Learn how AI and machine learning are revolutionizing this field.
Syllabus
-
- Introduction to Molecular Simulations
-- Overview of Molecular Dynamics (MD)
-- Importance of Reproducibility in Simulations
-- Role of Python in Molecular Simulations
- Python for Scientific Computing
-- Basic Python for Scientific Computing
-- Overview of Scientific Libraries in Python: NumPy, SciPy, and Matplotlib
- Introduction to OpenMM
-- Setting up OpenMM
-- Basics of Creating Simulations in OpenMM
-- Understanding Force Fields and System Topologies
- Running and Analyzing MD Simulations
-- Setting Up and Running Simulations
-- Analyzing Trajectories and Simulation Data
-- Visualization Techniques with Python
- Advanced Topics in Molecular Dynamics
-- Enhanced Sampling Methods
-- Free Energy Calculations
-- Multiscale Modeling
- Machine Learning in Molecular Simulations
-- Introduction to Machine Learning Concepts
-- Overview of AI Tools in Python: TensorFlow and PyTorch
-- Applications of Machine Learning in Molecular Dynamics
- Case Studies and Applications
-- Protein-Ligand Binding Studies
-- Membrane and Ion Channel Simulations
-- Integrating AI for Predictive Simulations
- Best Practices for Reproducible Research
-- Version Control with Git
-- Documentation and Notebook Practices
-- Packaging, Sharing, and Publishing Results
- Final Project
-- Designing a Reproducible Simulation Workflow
-- Implementing a Machine Learning Model in Simulations
-- Presentation and Peer Review of Projects
Taught by
Tags
On-Demand
