The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Enhanced Modeling via Network Theory: Adaptive Sampling of Markov State Models
Open accessAbstract
Computer simulations can complement experiments by providing insight into molecular kinetics with atomic resolution. Unfortunately, even the most powerful supercomputers can only simulate small systems for short timescales, leaving modeling of most biologically relevant systems and timescales intractable. In this work, however, we show that molecular simulations driven by adaptive sampling of networks called Markov State Models (MSMs) can yield tremendous time and resource savings, allowing previously intractable calculations to be performed on a routine basis on existing hardware. We also introduce a distance metric (based on the relative entropy) for comparing MSMs. We primarily employ this metric to judge the convergence of various sampling schemes but it could also be employed to assess the effects of perturbations to a system (e.g. determining how changing the temperature or making a mutation changes a system's dynamics).
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Cites
Elements of Information Theory
Cover, T. M., & Thomas, J. A. (2005) · doi:10.1002/047174882x · Cited by 13,791
Practical markov chain monte carlo
Geyer, C. J. (1992) · Statistical Science · doi:10.1214/ss/1177011137 · Cited by 2,045
T RANSITION P ATH S AMPLING : Throwing Ropes Over Rough Mountain Passes, in the Dark
Bolhuis, P. G., Chandler, D., Dellago, C., & Geissler, P. L. (2002) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.53.082301.113146 · Cited by 1,972
King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., Liakata, M., Markham, M., Pir, P., Soldatova, L. N., et al. (2009) · Science · doi:10.1126/science.1165620 · Cited by 679
Bowman, G. R., Beauchamp, K. A., Boxer, G., & Pande, V. S. (2009) · The Journal of Chemical Physics · doi:10.1063/1.3216567 · Cited by 396
Self-citation
Cited by
Markov models of molecular kinetics: Generation and validation
Prinz, J.-H., Wu, H., Sarich, M., Keller, B., Senne, M., Held, M., Chodera, J. D., Schütte, C., & Noé, F. (2011) · The Journal of Chemical Physics · doi:10.1063/1.3565032 · Cited by 1,275
Markov State Models: From an Art to a Science
Husic, B. E., & Pande, V. S. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.7b12191 · Cited by 886
Self-citationEverything you wanted to know about Markov State Models but were afraid to ask
Pande, V. S., Beauchamp, K., & Bowman, G. R. (2010) · Methods · doi:10.1016/j.ymeth.2010.06.002 · Cited by 698
Self-citationSalmaso, V., & Moro, S. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.00923 · Cited by 666
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
Salo-Ahen, O. M. H., Alanko, I., Bhadane, R., Bonvin, A. M. J. J., Honorato, R. V., Hossain, S., Juffer, A. H., Kabedev, A., Lahtela-Kakkonen, M., Larsen, A. S., et al. (2020) · Processes · doi:10.3390/pr9010071 · Cited by 659
Metadata
- Authors
- Bowman, G. R., Ensign, D. L., & Pande, V. S.
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-02-17
- Volume
- 6
- Issue
- 3
- Pages
- 787-794
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- OpenAlex
- W2016336300
- Cited by
- 245
- References
- 5
- FWCI
- 3.43
- Type
- journal article
- Language
- en
- Open access
- green
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