4.2.7. ENCORE Ensemble Similarity Calculations — MDAnalysis.analysis.encore
- Author:
Matteo Tiberti, Wouter Boomsma, Tone Bengtsen
- Year:
2015-2017
- Copyright:
GNU Public License v3
- Maintainer:
Matteo Tiberti <matteo.tiberti@gmail.com>, mtiberti on github
New in version 0.16.0.
The module contains implementations of similarity measures between protein ensembles described in [1]. The implementation and examples are described in [2].
The module includes facilities for handling ensembles and trajectories through
the Universe class, performing clustering or dimensionality reduction
of the ensemble space, estimating multivariate probability distributions from
the input data, and more. ENCORE can be used to compare experimental and
simulation-derived ensembles, as well as estimate the convergence of
trajectories from time-dependent simulations.
ENCORE includes three different methods for calculations of similarity measures between ensembles implemented in individual functions:
Harmonic Ensemble Similarity :
hes()Clustering Ensemble Similarity :
ces()Dimensional Reduction Ensemble Similarity :
dres()
as well as two methods to evaluate the convergence of trajectories:
Clustering based convergence evaluation :
ces_convergence()Dimensionality-reduction based convergence evaluation :
dres_convergence()
When using this module in published work please cite [2].
4.2.7.1. Modules
- 4.2.7.1.1. Ensemble Similarity Calculations —
MDAnalysis.analysis.encore.similarity - 4.2.7.1.2. Clustering
- 4.2.7.1.3. Dimensionality reduction
- 4.2.7.1.4. Distance Matrix calculation —
MDAnalysis.analysis.ensemble.confdistmatrix - 4.2.7.1.5. Covariance calculation —
encore.covariance - 4.2.7.1.6. bootstrap procedures —
MDAnalysis.analysis.ensemble.bootstrap - 4.2.7.1.7. Utility functions for ENCORE