Reaction Networks for Interstellar Chemical Modelling: Improvements and Challenges [PDF]
Space Science Reviews, 2010 Accepted for publication in Space Science ...
Wakelam, Valentine +12 more
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Journal of Cheminformatics, 2023 In recent years, it has been seen that artificial intelligence (AI) starts to bring revolutionary changes to chemical synthesis. However, the lack of suitable ways of representing chemical reactions and the scarceness of reaction data has limited the ...
Baiqing Li +8 more
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Improving Chemical Reaction Prediction with Unlabeled Data
Molecules, 2022 Predicting products of organic chemical reactions is useful in chemical sciences, especially when one or more reactants are new organics. However, the performance of traditional learning models heavily relies on high-quality labeled data.
Yu Xie +4 more
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Identification of functional differences in metabolic networks using comparative genomics and constraint-based models. [PDF]
PLoS ONE, 2012 Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms.
Joshua J Hamilton, Jennifer L Reed
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The Gompertz model revisited and modified using reaction networks: Mathematical analysis
Biomath, 2021 In the present work we discuss the usage of the framework of chemical reaction networks for the construction of dynamical models and their mathematical analysis.
Svetoslav Marinov Markov
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A global optimization method for model selection in chemical reactions networks [PDF]
Computers & Chemical Engineering, 2016 Model inference is a challenging problem in the analysis of chemical reactions networks. In order to empirically test which, out of a catalogue of proposed kinetic models, is governing a network of chemical reactions, the user can compare the empirical data obtained in one experiment against the theoretical values suggested by the models
Rafael Blanquero +3 more
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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
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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
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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
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