Automated network generation and analysis of biochemical reaction pathways using RING

Reaction Networks and the Metric Structure of Chemical Space(s)

“…Reaction networks play a central role in kinetic modeling of complex chemical reactions [19][20][21][22] and origins of life research. [23][24][25][26] The analysis of their graph structures has provided insights into mechanistic complexity and catalysis.…”

Discerning complex reaction networks using automated generators

“…BioTRaNS was applied to predict the metabolite inventory and the interconnecting pathways resulting from exposure to chemicals in a mixture. Recently, RING was demonstrated to be applicable to biochemical processes, including the transformation of the five‐carbon sugar xylose to 2‐ketoglutarate, and the generation of N‐ and O‐glycosylation networks in mammalian cells …”

Moving from postdictive to predictive kinetics in reaction engineering

“…As discussed in the Perspective by 2018 Wilhelm Award winner Linda Broadbelt, 3 it is now often possible to write down all the important reactions in a detailed kinetic model using various automatic mechanism generation software packages 11‐20 . These computer‐generated reaction mechanisms are intended to include not just the molecules in the feed and the product streams, but also all the important reactive intermediates, as well as multiple side channels leading to byproducts (though sometimes some of the species are intentionally lumped 20 ).…”

“…For example, in a recent high‐fidelity model for H 2 combustion, it was found that including a large number of rate 25 and transport 26 parameters coming purely from quantum chemistry calculations, not inferred at all from experimental data, significantly improved the predictions of important properties such as flame speed 23 . Combining this new capability to compute model parameters from first principles with automatic reaction mechanism generation software 3,11‐20 makes it possible to predict the course of chemical reactions before doing any experiments, and to understand processes that are happening in an experimental system even if they are impractical to measure. This new predictive capability has many implications for the future of Reaction Engineering, for industrial practice, and for how chemical engineers should be educated, some of which are highlighted below.…”