IPython Notebook Tutorials

These IPython (http://ipython.org) notebooks show the usage of the PyEMMA API in action and also describe the workflow of Markov model building.

Pentapeptide

• Markov state model for pentapeptide
  • Load pentapeptide coordinates and select features
• TICA and clustering
• Implied timescales
• Estimate MSM
• PCCA

BPTI

• Markov state model for BPTI
  • BPTI 1 ms trajectory - load data
  • time-lagged independent component analysis (TICA)
  • Clustering the data
  • Let’s play
  • 1) Different clustering methods
  • 2) PCA vs TICA
  • 3) Do everything in memory
  • 4) Do everything as a pipeline
  • 5) Striding
  • 6) Different coordinates
  • MSM estimation
  • MSM
  • Spectral analysis
  • MSM trajectory
  • Representative Structures
  • Experimental observables
  • Transition pathways and Committors
  • References