PNNARMA model: an alternative to phenomenological models in chemical reactors [PDF]
, 2001 This paper is focused on the development of non-linear neural models able to provide appropriate predictions when acting as process simulators. Parallel identification models can be used for this purpose.
J.M. Zaldı́var +5 more
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Accelerating Reaction Network Explorations with Automated Reaction Template Extraction and Application [PDF]
, 2023 Autonomously exploring chemical reaction networks with first-principles methods can generate vast data. Especially autonomous explorations without tight constraints risk getting trapped in regions of reaction networks that are not of interest.
Jan Patrick, Unsleber
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Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson’s Catalyst Case
Molecules, 2023 Ab initio kinetic studies are important to understand and design novel chemical reactions. While the Artificial Force Induced Reaction (AFIR) method provides a convenient and efficient framework for kinetic studies, accurate explorations of reaction path
Ruben Staub +4 more
doaj +1 more source
Bayesian chemical reaction neural network for autonomous kinetic uncertainty quantification
, 2023 We develop Bayesian Chemical Reaction Neural Network (B-CRNN), a method to infer chemical reaction models and provide the associated uncertainty purely from data without prior knowledge of reaction templates.
Koenig, Benjamin C +3 more
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Persistence and stability of generalized ribosome flow models with time-varying transition rates.
PLoS ONE, 2023 In this paper some important qualitative dynamical properties of generalized ribosome flow models are studied. Ribosome flow models known from the literature are generalized by allowing an arbitrary directed network structure between compartments, and by
Mihály A Vághy, Gábor Szederkényi
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Mathematical Methods for Modeling Chemical Reaction Networks [PDF]
, 2016 Abstract Cancer’s cellular behavior is driven by alterations in the processes that cells use to sense and respond to diverse stimuli. Underlying these processes are a series of chemical processes (enzyme-substrate, protein-protein, etc.).
Carden Jr-PSOC Me, Justin +4 more
openaire +1 more source
Systematic assignment of thermodynamic constraints in metabolic network models [PDF]
, 2006 Background: The availability of genome sequences for many organisms enabled the reconstruction of several genome-scale metabolic network models. Currently, significant efforts are put into the automated reconstruction of such models.
Kümmel, Anne, +12 more
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Autonomous kinetic modeling of biomass pyrolysis using chemical reaction neural networks [PDF]
Combustion and Flame, 2022 Modeling the burning processes of biomass such as wood, grass, and crops is crucial for the modeling and prediction of wildland and urban fire behavior. Despite its importance, the burning of solid fuels remains poorly understood, which can be partly attributed to the unknown chemical kinetics of most solid fuels.
Weiqi Ji +3 more
openaire +4 more sources
Exploring Chemical Reaction Space With Reaction Difference Fingerprints and Parametric t-SNE [PDF]
, 2021 Humans prefer visual representations for the analysis of large databases. In this work, we suggest a method for the visualization of the chemical reaction space.
Sergey, Sosnin +2 more
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Chemical master equation and Langevin regimes for a gene transcription model [PDF]
, 2008 Gene transcription models must take account of intrinsic stochasticity. The Chemical Master Equation framework is based on modelling assumptions that are highly appropriate for this context, and the Stochastic Simulation Algorithm (also known as ...
Higham, Desmond J., Khanin, Raya
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