A Python implementation for Dynamical Network Analysis.
Project description
Dynamical Network Analysis
The Python implementation of Dynamical Network Analysis was bulit 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.rst
.
Tutorial
For an introduction to this implementation, a jupyter notebook tutorial has been prepared and released along with its latest publication:
- Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories. In revision (2020).
Resources and References
For the background on Dynamical Network Analysis, see the following papers that describe its development:
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Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories. In revision (2020).
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Experimental and computational determination of tRNA dynamics. FEBS Letters (2010). DOI:
10.1016/j.febslet.2009.11.061 <https://doi.org/10.1016/j.febslet.2009.11.061>
_ -
Exit strategies for charged tRNA from GluRS. JMB (2010). DOI:
10.1016/j.jmb.2010.02.003 <https://doi.org/10.1016/j.jmb.2010.02.003>
_ -
Dynamical Networks in tRNA:protein complexes. PNAS (2009). DOI:
10.1073/pnas.0810961106 <https://doi.org/10.1073/pnas.0810961106>
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