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Biophys J. 2017 Jan 10;112(1):10-15. doi: 10.1016/j.bpj.2016.10.042.

MSMBuilder: Statistical Models for Biomolecular Dynamics.

Author information

1
Department of Chemistry, Stanford University, Stanford, California.
2
Program in Biophysics, Stanford University, Stanford, California.
3
Memorial Sloan Kettering Cancer Center, New York, New York.
4
Department of Chemistry, Stanford University, Stanford, California. Electronic address: robert.mcgibbon@deshawresearch.com.
5
Department of Chemistry, Stanford University, Stanford, California; Program in Biophysics, Stanford University, Stanford, California; Department of Computer Science, Stanford University, Stanford, California; Department of Structural Biology, Stanford University, Stanford, California. Electronic address: pande@stanford.edu.

Abstract

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.

PMID:
28076801
PMCID:
PMC5232355
DOI:
10.1016/j.bpj.2016.10.042
[Indexed for MEDLINE]
Free PMC Article

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