dynetan 2.6.0

A Python implementation for Dynamical Network Analysis.

Dynamical Network Analysis

The Python implementation of Dynamical Network Analysis was built to provide all functionalities necessary to the analysis of Molecular Dynamics (MD) simulations using the Dynamical Network Analysis method.

Install

Install the latest version of Dynamical Network Analysis:

$ pip install dynetan

For additional details, please see INSTALL.md.

Tutorial

Several jupyter notebook tutorials have been prepared as an introduction to this package and were released in an independent repository:

https://gitlab.com/comp-biochem-csu/dynetan_tutorial

Documentation

The full documentation can be found at https://dynamical-network-analysis.readthedocs.io/en/latest/index.html

Resources and References

For the background on Dynamical Network Analysis, see the following papers that describe its development:

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

• 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