Dynamical Network Analysis

This package was built to provide an updated and enhanced Python implementation of the Dynamical Network Analysis method, for the analysis of Molecular Dynamics simulations. The package was optimized for interactive data analysis and visualization through Jupyter Notebooks (see Tutorial), and provides an interface for rendering publication-quality figures using VMD. It allows for extensive customization of analysis workflows to suit research-specific needs.

Contents:

• Introduction
  • Scientific Background
  • Dynamical Network Analysis
  • Current Implementation
• Installation
  • Installing with pip
  • Requirements
  • Build the package from source:
  • Troubleshooting installation with pip
• Tutorial
• Usage
• Citing
• Reference
  • Process Trajectory Data
  • Save and Load Data
  • Contact Detection
  • Generalized Correlations
  • Network Properties
  • Toolkit
  • Visualization

Indices and tables

• Index

• Module Index

• Search Page

Resources and References

Citing

To cite this package please use the following publication:

• Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories. JCP (2020). DOI: 10.1063/5.0018980

For further discussion and scientific background, please refer to:

• Experimental and computational determination of tRNA dynamics. FEBS Letters (2010). DOI: 10.1016/j.febslet.2009.11.061

• Exit strategies for charged tRNA from GluRS. JMB (2010). DOI: 10.1016/j.jmb.2010.02.003

• Dynamical Networks in tRNA:protein complexes. PNAS (2009). DOI: 10.1073/pnas.0810961106

Last Updated

Date

Aug 23, 2023