MSMBuilder: Statistical Models for Biomolecular Dynamics

• Published in: Biophysical journal Vol. 112; no. 1; pp. 10 - 15
• Main Authors: Harrigan, Matthew P., Sultan, Mohammad M., Hernández, Carlos X., Husic, Brooke E., Eastman, Peter, Schwantes, Christian R., Beauchamp, Kyle A., McGibbon, Robert T., Pande, Vijay S.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 10.01.2017; Biophysical Society; The Biophysical Society
• Subjects: Algorithms; Application programming interface; Computational Tool; Markov analysis; Markov Chains; Models, Statistical; Molecular Dynamics Simulation; Protein Conformation; Protein folding; Simulation; Software; src-Family Kinases - chemistry; src-Family Kinases - metabolism; Time series
• ISSN: 0006-3495; 1542-0086
• DOI: 10.1016/j.bpj.2016.10.042

MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis of atomistic simulations of biomolecular dynamics such as protein folding and conformational change. MSMBuilder is named for its ability to construct Markov state models (MSMs), a class of models that has gained favor among computational biophysicists. In addition to both well-established and newer MSM methods, the package includes complementary algorithms for understanding time-series data such as hidden Markov models and time-structure based independent component analysis. MSMBuilder boasts an easy to use command-line interface, as well as clear and consistent abstractions through its Python application programming interface. MSMBuilder was developed with careful consideration for compatibility with the broader machine learning community by following the design of scikit-learn. The package is used primarily by practitioners of molecular dynamics, but is just as applicable to other computational or experimental time-series measurements.