Reproducible Molecular Simulations with Python

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

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Subjects

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