ArticleThe journal of physical chemistry. B2015
Optimal Dimensionality Reduction of Multistate Kinetic and Markov-State Models.
Article in The journal of physical chemistry. B, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Article
- Identification and quantification of irreversibility in stochastic systems.Physical chemistry chemical physics : PCCP · 2026Review
- Unveiling hidden intermediate states in protein folding with AI-based conditional transition clustering.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Helix Folding in One Dimension: Effects of Proline Co-Solvent on Free Energy Landscape of Hydrogen Bond Dynamics in Alanine Peptides.Life (Basel, Switzerland) · 2025Article
- Ion Channel Reaction Networks: Dielectric Screening and the Importance of Off-Pathway Flux.Journal of chemical theory and computation · 2025Article
- Markov-Type State Models to Describe Non-Markovian Dynamics.Journal of chemical theory and computation · 2025Article
- Supercomputing in the biological sciences: Toward Zettascale and Yottascale simulations.Current opinion in structural biology · 2024Review
- Spectral Map for Slow Collective Variables, Markovian Dynamics, and Transition State Ensembles.Journal of chemical theory and computation · 2024Article
- Kemeny Constant-Based Optimization of Network Clustering Using Graph Neural Networks.The journal of physical chemistry. B · 2024Article
- An encompassed representation of timescale hierarchies in first-order reaction network.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Markov State Models: To Optimize or Not to Optimize.Journal of chemical theory and computation · 2024Article
- Integrative generalized master equation: A method to study long-timescale biomolecular dynamics via the integrals of memory kernels.The Journal of chemical physics · 2023Article
- Building insightful, memory-enriched models to capture long-time biochemical processes from short-time simulations.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Optimization of non-equilibrium self-assembly protocols using Markov state models.The Journal of chemical physics · 2022Article
- Deep learning to decompose macromolecules into independent Markovian domains.Nature communications · 2022Article
- Multiscale kinetic analysis of proteins.Current opinion in structural biology · 2022Review
- Dissecting Multiple Pathways in the Relaxation Dynamics of Helix <==> Coil Transitions with Optimum Dimensionality Reduction.Biomolecules · 2021Review
- String Method with Swarms-of-Trajectories, Mean Drifts, Lag Time, and Committor.The journal of physical chemistry. A · 2021Article
- Temperature-dependent kinetic pathways of heterogeneous ice nucleation competing between classical and non-classical nucleation.Nature communications · 2021Article
- Computational IR Spectroscopy of Insulin Dimer Structure and Conformational Heterogeneity.The journal of physical chemistry. B · 2021Article
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2 authors.
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Abstract
We develop a systematic procedure for obtaining rate and transition matrices that optimally describe the dynamics of aggregated superstates formed by combining (clustering or lumping) microstates. These reduced dynamical models are constructed by matching the time-dependent occupancy-number correlation functions of the superstates in the full and aggregated systems. Identical results are obtained by using a projection operator formalism. The reduced dynamic models are exact for all times in their full non-Markovian formulation. In the approximate Markovian limit, we derive simple analytic expressions for the reduced rate or Markov transition matrices that lead to exact auto- and cross-relaxation times. These reduced Markovian models strike an optimal balance between matching the dynamics at short and long times. We also discuss how this approach can be used in a hierarchical procedure of constructing optimal superstates through aggregation of microstates. The results of the general reduced-matrix theory are illustrated with applications to simple model systems and a more complex master-equation model of peptide folding derived previously from atomistic molecular dynamics simulations. We find that the reduced models faithfully capture the dynamics of the full systems, producing substantial improvements over the common local-equilibrium approximation.
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