Learning Chemical Reaction Networks from Trajectory Data-Reference-Cited by-同舟云学术

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Learning Chemical Reaction Networks from Trajectory Data

Published:2019-01 Issue:4 Volume:18 Page:2000-2046
ISSN:1536-0040
Container-title:SIAM Journal on Applied Dynamical Systems
language:en
Short-container-title:SIAM J. Appl. Dyn. Syst.

Author:

Zhang Wei,Klus Stefan,Conrad Tim,Schütte Christof

Funder

Einstein Center of Mathematics

Deutsche Forschungsgemeinschaft

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Modeling and Simulation,Analysis

Link

https://epubs.siam.org/doi/pdf/10.1137/19M1265880

Reference39 articles.

1. A Tutorial on Chemical Reaction Network Dynamics

2. Systems biology: parameter estimation for biochemical models

3. Asymptotic analysis of multiscale approximations to reaction networks

4. Network biology: understanding the cell's functional organization

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1. Error-Controlled Coarse-Graining Dynamics with Mean-Field Randomization;Journal of Chemical Theory and Computation;2023-10-31

2. A review of automated and data-driven approaches for pathway determination and reaction monitoring in complex chemical systems;Digital Chemical Engineering;2022-03

3. When machine learning meets multiscale modeling in chemical reactions;The Journal of Chemical Physics;2020-09-07

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