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2dmodel_path_analysis

Jupyter notebook with 2D test potential energy landscape for performing model biased simulations combined with pathway analysis.

clustering

Robust and stable clustering of molecular dynamics simulation trajectories.

data-driven-langevin

Program to run the data driven Langevin equation as described in Schaudinnus et al., Phys. Rev. Lett. 115, 050602 (2015) or Rzepiela et al. J. Chem. Phys. 141, 241102 (2014). The basic publication is Hegger and Stock, J. Chem. Phys. 130, 034106 (2009) .

dctmd

Analysis framework of dissipation-corrected targeted molecular dynamics (dcTMD) simulations.

dctmd_scripts_v1.0

dissipation corrected targeted molecular dynamics

fastpca

Fast, parallelized implementation of Principal Component Analysis with constant memory consumption for large data sets.

forceatlas2

Fastest Gephi's ForceAtlas2 graph layout algorithm implemented for Python and NetworkX

hp35

Selecting Features for Markov Modeling: A Case Study on HP35

hp35-benchmark

Benchmarking dimensionality reduction methods and clustering on HP35-DESRES

hp35-desres

DESRES trajectory of wild type HP-35 at 360K

langevin_t_boost

Includes C++ code to run Markovian Langevin equations in units compatible with the dcTMD correction scripts available at www.moldyn.uni-freiburg.de/software/software.html. In addition, a jupyter notebook can be found which estimates the error of rates at 300 K from T-boosting calculations.

mosaic

Correlation-based feature selection of Molecular Dynamics simulations

msmhelper

Helper function for Markov State Models

msmpathfinder

Finding pathways from an Markov State Model

normi

Generalized Kraskov Estimator for Normalized Mutual Information

python-packaging

An example python packaging

ramacolor

The ramacolor script produce plots as proposed in Sittel et al., J. Chem. Theory Comput 12, 2426 (2016)

rescaled_dle_and_pre_averaging

Includes implementations of the data-driven Langevin equation with and without rescaling of the friction. Includes also data-driven Langevin codes which work with pre-averaged data. Finally, programs can be found to produce Markovian and generalized Langevin dynamics in case the fields are already known. The generalized Langevin equation assumes a mono-exponential memory kernel.

tutorial_dctmd

Tutorial for the usage of the dcTMD approach and Langevin simulations employing the trypsin-benzamidine complex as example.

xgbanalysis

Machine-Learning analysis of large data sets from molecular dynamics simulation