MSMBuilder: Statistical Models for Biomolecular Dynamics
Open accessPreprint — published as 10.1016/j.bpj.2016.10.042 · Paper page
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 (HMMs) and time-structure based independent component analysis (tICA). MSMBuilder boasts an easy to use command-line interface, as well as clear and consistent abstractions through its Python API (application programming interface). MSMBuilder is 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. http://msmbuilder.org
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Identification of slow molecular order parameters for Markov model construction
Pérez-Hernández, G., Paul, F., Giorgino, T., De Fabritiis, G., & Noé, F. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4811489 · Cited by 990 · cited 1× · see citing works
“In practice, this dimensionality reduction has proven to be very useful for capturing slow, biophysical conformational changes (20,21).”
BackgroundMarkov state models of biomolecular conformational dynamics
Chodera, J. D., & Noé, F. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.04.002 · Cited by 776 · see citing works
Schwantes, C. R., & Pande, V. S. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct300878a · Cited by 597 · cited 1× · see citing works
“In practice, this dimensionality reduction has proven to be very useful for capturing slow, biophysical conformational changes (20,21).”
BackgroundSelf-citationRobust Perron cluster analysis in conformation dynamics
Deuflhard, P., & Weber, M. (2005) · Linear Algebra and its Applications · doi:10.1016/j.laa.2004.10.026 · Cited by 506 · cited 1× · see citing works
“…macrostates by applying robust Perron clustering analysis (PCCA þ ) to our MSM. PCCA þ is a spectral clustering method that lumps MSM states into an arbitrary number of metastable macrostates, facilitating qualitative analysis of rates and populations among biologically relevant macro-states (28).”
Method
Flagged first, then by citations
- Authors
- Harrigan, M. P., Sultan, M. M., Hernández, C. X., Husic, B. E., Eastman, P., Schwantes, C. R., Beauchamp, K. A., McGibbon, R. T., & Pande, V. S.
- Affiliations
- Stanford University (US)
- Memorial Sloan Kettering Cancer Center (US)
- Corresponding author
- McGibbon, Robert T.
- Pande, Vijay S.
- ORCID
- Venue
- Biophysical Journal
- Publisher
- openRxiv
- Published
- 2016-10-27
- Volume
- 112
- Issue
- 1
- Pages
- 10-15
- ISSN
- 0006-3495 (ISSN-L)
- PMC
- PMC5232355
- OpenAlex
- W2570547882
- Cited by
- 277
- References
- 4
- Citations by year
- 2026: 16 · 2025: 26 · 2024: 24 · 2023: 19 · 2022: 39 · 2021: 30 · 2020: 23 · 2019: 28 · 2018: 48 · 2017: 24
- FWCI
- 13.74
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Biophysical Journal (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation ((DGE-114747, 0954714, 114747)
- Starr Foundation (I8-A8-058)
- National Institutes of Health (5u19ai109662-05, P30CA008747, DGE-114747, U19 AI109662)
- National Institute of General Medical Sciences (T32GM008294, R01GM062868)
- National Institute of Allergy and Infectious Diseases (U19-AI109662)
- National Science Foundation Graduate Research Fellowship Program (DGE‐114747)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- Markov state models, biomolecular dynamics, protein folding, conformational change, atomistic simulation, hidden Markov models, independent component analysis, time series analysis, high-dimensional time series, Python, scikit-learn compatibility, machine learning
- MeSH terms
- CSK Tyrosine-Protein Kinase, Markov Chains, Protein Conformation, Software, Models, Statistical, src-Family Kinases, Molecular Dynamics Simulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
