ArticleThe Journal of chemical physics2019
Galerkin approximation of dynamical quantities using trajectory data.
Article in The Journal of chemical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed.
- A continuous-space analytical framework for committor functions from molecular dynamics.The Journal of chemical physics · 2026Article
- An Exact Multiple-Time-Step Variational Formulation for the Committor and the Transition Rate.The journal of physical chemistry. B · 2026Article
- Reaction Coordinates Are Optimal Channels of Energy Flow.Annual review of physical chemistry · 2025Review
- Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics.The Journal of chemical physics · 2025Article
- Article
- Analysis of the Dynamics of a Complex, Multipathway Reaction: Insulin Dimer Dissociation.The journal of physical chemistry. B · 2024Article
- Temperature-dependent fold-switching mechanism of the circadian clock protein KaiB.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Spectral Map for Slow Collective Variables, Markovian Dynamics, and Transition State Ensembles.Journal of chemical theory and computation · 2024Article
- BAD-NEUS: Rapidly converging trajectory stratification.The Journal of chemical physics · 2024Article
- Good Rates From Bad Coordinates: The Exponential Average Time-dependent Rate Approach.Journal of chemical theory and computation · 2024Article
- Accurate estimates of dynamical statistics using memory.The Journal of chemical physics · 2024Article
- Dynamics of activation in the voltage-sensing domain of Ciona intestinalis phosphatase Ci-VSP.Nature communications · 2024Article
- Predicting rare events using neural networks and short-trajectory data.Journal of computational physics · 2023Article
- Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction.The Journal of chemical physics · 2023Article
- Committor-Consistent Variational String Method.The journal of physical chemistry letters · 2022Article
- Augmented transition path theory for sequences of events.The Journal of chemical physics · 2022Article
- Data-driven prediction in dynamical systems: recent developments.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
- Computing transition path theory quantities with trajectory stratification.The Journal of chemical physics · 2022Article
- Transition rate theory, spectral analysis, and reactive paths.The Journal of chemical physics · 2022Article
- A gentle introduction to the non-equilibrium physics of trajectories: Theory, algorithms, and biomolecular applications.American journal of physics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Understanding chemical mechanisms requires estimating dynamical statistics such as expected hitting times, reaction rates, and committors. Here, we present a general framework for calculating these dynamical quantities by approximating boundary value problems using dynamical operators with a Galerkin expansion. A specific choice of basis set in the expansion corresponds to the estimation of dynamical quantities using a Markov state model. More generally, the boundary conditions impose restrictions on the choice of basis sets. We demonstrate how an alternative basis can be constructed using ideas from diffusion maps. In our numerical experiments, this basis gives results of comparable or better accuracy to Markov state models. Additionally, we show that delay embedding can reduce the information lost when projecting the system's dynamics for model construction; this improves estimates of dynamical statistics considerably over the standard practice of increasing the lag time.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.