Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework.

ABSTRACT: Current metabolic modeling tools suffer from a variety of limitations, from scalability to simplifying assumptions, that preclude their use in many applications. We recently created a modeling framework, Linear Kinetics-Dynamic Flux Balance Analysis (LK-DFBA), that addresses a key gap: capturing metabolite dynamics and regulation while retaining a potentially scalable linear programming structure. Key to this framework's success are the linear kinetics and regulatory constraints imposed on the system. However, while the linearity of these constraints reduces computational complexity, it may not accurately capture the behavior of many biochemical systems. Here, we developed three new classes of LK-DFBA constraints to better model interactions between metabolites and the reactions they regul

SUBMITTER: Lee JY 

PROVIDER: S-EPMC8760257 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature