%0 Journal Article %1 Feng2015WEvsMSM %A Feng, Haoyun %A Costaouec, Ronan %A Darve, Eric %A Izaguirre, Jesús A. %B The Journal of Chemical Physics %D 2015 %I American Institute of Physics %J The Journal of Chemical Physics %K MSMs WE enhanced-sampling markov-state-models weighted-ensemble %N 21 %P 214113-- %R 10.1063/1.4921890 %T A comparison of weighted ensemble and Markov state model methodologies %U https://doi.org/10.1063/1.4921890 %V 142 %X Computation of reaction rates and elucidation of reaction mechanisms are two of the main goals of molecular dynamics (MD) and related simulation methods. Since it is time consuming to study reaction mechanisms over long time scales using brute force MD simulations, two ensemble methods, Markov State Models (MSMs) and Weighted Ensemble (WE), have been proposed to accelerate the procedure. Both approaches require clustering of microscopic configurations into networks of “macro-states” for different purposes. MSMs model a discretization of the original dynamics on the macro-states. Accuracy of the model significantly relies on the boundaries of macro-states. On the other hand, WE uses macro-states to formulate a resampling procedure that kills and splits MD simulations for achieving better efficiency of sampling. Comparing to MSMs, accuracy of WE rate predictions is less sensitive to the definition of macro-states. Rigorous numerical experiments using alanine dipeptide and penta-alanine support our analyses....

@article{Feng2015WEvsMSM, abstract = {Computation of reaction rates and elucidation of reaction mechanisms are two of the main goals of molecular dynamics (MD) and related simulation methods. Since it is time consuming to study reaction mechanisms over long time scales using brute force MD simulations, two ensemble methods, Markov State Models (MSMs) and Weighted Ensemble (WE), have been proposed to accelerate the procedure. Both approaches require clustering of microscopic configurations into networks of “macro-states” for different purposes. MSMs model a discretization of the original dynamics on the macro-states. Accuracy of the model significantly relies on the boundaries of macro-states. On the other hand, WE uses macro-states to formulate a resampling procedure that kills and splits MD simulations for achieving better efficiency of sampling. Comparing to MSMs, accuracy of WE rate predictions is less sensitive to the definition of macro-states. Rigorous numerical experiments using alanine dipeptide and penta-alanine support our analyses....}, added-at = {2018-04-27T23:24:18.000+0200}, author = {Feng, Haoyun and Costaouec, Ronan and Darve, Eric and Izaguirre, Jesús A.}, biburl = {https://www.bibsonomy.org/bibtex/27254810102e347c86af6353669918013/salotz}, booktitle = {The Journal of Chemical Physics}, comment = {doi: 10.1063/1.4921890}, description = {A comparison of weighted ensemble and Markov state model methodologies: The Journal of Chemical Physics: Vol 142, No 21}, doi = {10.1063/1.4921890}, interhash = {3ed2a8f6f65095a6c9a6b774f0eb6c1a}, intrahash = {7254810102e347c86af6353669918013}, issn = {00219606}, journal = {The Journal of Chemical Physics}, keywords = {MSMs WE enhanced-sampling markov-state-models weighted-ensemble}, month = jun, number = 21, pages = {214113--}, publisher = {American Institute of Physics}, timestamp = {2018-04-27T23:24:18.000+0200}, title = {A comparison of weighted ensemble and Markov state model methodologies}, url = {https://doi.org/10.1063/1.4921890}, volume = 142, year = 2015 }