MDEntropy¶

MDEntropy is a python library that allows users to perform information-theoretic analyses on molecular dynamics (MD) trajectories. It includes methods to calculate:

Bias-Corrected Entropy
Conditional Entropy
Mutual Information
Normalized Mutual Information
Conditional Mutual Information
Normalized Conditional Mutual Information

MDEntropy is actively being developed by researchers at Stanford University, with primary application areas in computational protein dynamics and drug design, and distributed under the MIT License. All development takes place on GitHub.

To cite MDEntropy, please use the following reference:

@article{mdentropy,
  author       = {Carlos X. Hern{\'{a}}ndez and Vijay S. Pande},
  title        = {{MDEntropy: Information-Theoretic Analyses for Molecular Dynamics}},
  month        = nov,
  year         = 2017,
  doi          = {10.21105/joss.00427},
  url          = {https://doi.org/10.21105/joss.00427}
}