Results 61 to 70 of about 17,173,168 (192)
FRECKLL: Full and Reduced Exoplanet Chemical Kinetics DistiLLed
The Astrophysical JournalWe introduce a new Python 1D chemical kinetic code, Full and Reduced Exoplanet Chemical Kinetics distiLLed ( FRECKLL ), to evolve large chemical networks efficiently.
Ahmed Faris Al-Refaie +3 more
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Thermodynamics of random reaction networks. [PDF]
PLoS ONE, 2015 Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of ...
Jakob Fischer +2 more
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PLoS ONE, 2012 The inference of reaction rate parameters in biochemical network models from time series concentration data is a central task in computational systems biology.
Philipp Kügler
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The Astrophysical JournalWe present a neural-network emulator for the thermal and chemical evolution in Population III star formation. The emulator accurately reproduces the thermochemical evolution over a wide density range spanning 21 orders of magnitude (10 ^−3 –10 ^18 cm ^−3
Sojun Ono, Kazuyuki Sugimura
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Uncoupled analysis of stochastic reaction networks in fluctuating environments. [PDF]
PLoS Computational Biology, 2014 The dynamics of stochastic reaction networks within cells are inevitably modulated by factors considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy numbers for a gene regulatory network. While several recent studies
Christoph Zechner, Heinz Koeppl
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Physics-informed machine learning for automatic model reduction in chemical reaction networks
Scientific ReportsPhysics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computational
Joseph Pateras +4 more
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Physics-constrained machine learning for reduced composition space chemical kinetics
Data-Centric EngineeringModeling detailed chemical kinetics is a primary challenge in combustion simulations. We present a novel framework to enforce physical constraints, specifically total mass and elemental conservation, during the reaction of ML models’ training for the ...
Anuj Kumar, Tarek Echekki
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ABC(SMC)$$^2$$: Simultaneous Inference and Model Checking of Chemical Reaction Networks [PDF]
, 2020 We present an approach that simultaneously infers model parameters while statistically verifying properties of interest to chemical reaction networks, which we observe through data and we model as parametrised continuous-time Markov Chains. The new approach simultaneously integrates learning models from data, done by likelihood-free Bayesian inference,
Molyneux, GW, Abate, A
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Basal State Calibration of a Chemical Reaction Network Model for Autophagy
International Journal of Molecular SciencesThe modulation of autophagy plays a dual role in tumor cells, with the potential to both promote and suppress tumor proliferation. In order to gain a deeper understanding of the nature of autophagy, we have developed a chemical reaction kinetic model of autophagy and apoptosis based on the mass action kinetic models that have been previously described ...
Bence Hajdú, Orsolya Kapuy, Tibor Nagy
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Port-Hamiltonian modeling of non-isothermal chemical reaction networks [PDF]
Journal of Mathematical Chemistry, 2018 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, Li +2 more
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