A meaningful path finding method without specific starting metabolite

Zhiyuan Wan

doi:10.1117/12.2658180

23 November 2022 A meaningful path finding method without specific starting metabolite

Zhiyuan Wan

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 124542Q (2022) https://doi.org/10.1117/12.2658180
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

Identifying the metabolic pathways through computation is critical in metabolic engineering for the design of synthetic pathways. The constraint-based pathfinding of searching the metabolic pathway from a given starting metabolite to a target metabolite has been broadly used to find the metabolic pathways of synthesizing valuable metabolites, but few people have committed to adjusting a mixed integer linear program (MILP) model to search for the metabolic pathways from arbitrary starting metabolites to a target metabolite. In this paper, we present a novel metabolic pathway prediction method for discovering the metabolic pathway from arbitrary metabolites to a target metabolite in an adjusted metabolic network according to the feature of metabolites. This has the potential to enhance the biochemical correlation of metabolic pathways significantly. To summarize, our method is a valuable metabolic pathway prediction method for identifying alternative metabolic pathways and further improve the study of metabolic pathway prediction methods from arbitrary starting metabolites to the target metabolite.

Citation Download Citation

Zhiyuan Wan "A meaningful path finding method without specific starting metabolite", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 124542Q (23 November 2022); https://doi.org/10.1117/12.2658180

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Chemical species

Bacteria

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Detection and tracking algorithms

Yeast

Bioinformatics

Carbon

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