This is a private project. You must be a member to view its contents.

Provide an easy and automatic way to construct Markov State Models of biological datasets.

Constructing human comprehensible Markov state models(MSMs) to understand the dynamics of biomolecules can be a difficult task, mainly due to the rouged nature of its inherent energy landscape. This project provides a python implementation of the Super-level-set Hierarchical Clustering algorithm, originally described by Huang et. al. This program automates the discovery of metastable states and is intended to be an extension to the SimTK MSMbuilder.